@@ -30,7 +30,7 @@ Like other built-in skills, a custom **AML** skill has inputs and outputs. The i
 > * `503 Service Unavailable`
 > * `429 Too Many Requests`
 
-You can call the **AML** skill with the 2024-07-01 stable API version or an equivalent Azure SDK. For connections to the model catalog in the Azure AI Foundry portal, use the 2024-05-01-preview API version or later.
+You can call the **AML** skill with the stable REST API version or an equivalent Azure SDK. For connections to the model catalog in the Azure AI Foundry portal, use a preview API version.
 
 ## AML skill for models in Azure AI Foundry
 

@@ -235,7 +235,7 @@ Enrichments are billable operations. If you no longer need to call Azure AI serv
 1. Remove the key in the body of the definition, and then send the request:
 
     ```http
-    PUT https://[servicename].search.windows.net/skillsets/[skillset name]?api-version=2024-07-01
+    PUT https://[servicename].search.windows.net/skillsets/[skillset name]?api-version=2025-09-01
     api-key: [admin key]
     Content-Type: application/json
     {

@@ -45,12 +45,12 @@ Parameters are case-sensitive.
 
 | Inputs | Description |
 |---------------------|-------------|
-| `resourceUri` | The URI of the model provider. This parameter only supports URLs with the `openai.azure.com` domain, such as `https://<resourcename>.openai.azure.com`. If your Azure OpenAI endpoint has a URL with the `cognitiveservices.azure.com` domain, such as `https://<resourcename>.cognitiveservices.azure.com`, you must create a [custom subdomain](/azure/ai-services/openai/how-to/use-your-data-securely#enabled-custom-subdomain) with `openai.azure.com` for the Azure OpenAI resource and use `https://<resourcename>.openai.azure.com` instead. This field is required if your Azure OpenAI resource is deployed behind a private endpoint or uses Virtual Network (VNet) integration. [Azure API Management](/azure/api-management/api-management-key-concepts) endpoints are supported with URL `https://<resourcename>.azure-api.net `. Shared private links aren't supported for API Management endpoints.
+| `resourceUri` | Required. The URI of the model provider. This parameter only supports URLs with the `openai.azure.com` domain, such as `https://<resourcename>.openai.azure.com`. If your Azure OpenAI endpoint has a URL with the `cognitiveservices.azure.com` domain, such as `https://<resourcename>.cognitiveservices.azure.com`, you must create a [custom subdomain](/azure/ai-services/openai/how-to/use-your-data-securely#enabled-custom-subdomain) with `openai.azure.com` for the Azure OpenAI resource and use `https://<resourcename>.openai.azure.com` instead. This field is required if your Azure OpenAI resource is deployed behind a private endpoint or uses Virtual Network (VNet) integration. [Azure API Management](/azure/api-management/api-management-key-concepts) endpoints are supported with URL `https://<resourcename>.azure-api.net `. Shared private links aren't supported for API Management endpoints.
 | `apiKey`   |  The secret key used to access the model. If you provide a key, leave `authIdentity` empty. If you set both the `apiKey` and `authIdentity`, the `apiKey` is used on the connection. |
-| `deploymentId`   | The name of the deployed Azure OpenAI embedding model. The model should be an embedding model, such as text-embedding-ada-002. See the [List of Azure OpenAI models](/azure/ai-services/openai/concepts/models) for supported models.|
+| `deploymentId`   | Required. The name of the deployed Azure OpenAI embedding model. The model should be an embedding model, such as text-embedding-ada-002. See the [List of Azure OpenAI models](/azure/ai-services/openai/concepts/models) for supported models.|
 | `authIdentity`   | A user-managed identity used by the search service for connecting to Azure OpenAI. You can use either a [system or user managed identity](search-how-to-managed-identities.md). To use a system managed identity, leave `apiKey` and `authIdentity` blank. The system-managed identity is used automatically. A managed identity must have [Cognitive Services OpenAI User](/azure/ai-services/openai/how-to/role-based-access-control#azure-openai-roles) permissions to send text to Azure OpenAI. |
-| `modelName` | This property is required if your skillset is created using the 2024-05-01-preview or 2024-07-01 REST API. Set this property to the deployment name of an Azure OpenAI embedding model deployed on the provider specified through `resourceUri` and identified through `deploymentId`. Currently, the supported values are `text-embedding-ada-002`, `text-embedding-3-large`, and `text-embedding-3-small`.  |
-| `dimensions` | Optional, starting in the 2024-05-01-preview REST API, the dimensions of embeddings that you would like to generate, assuming the model supports a range of dimensions. Supported ranges are listed below, and currently only apply to the text-embedding-3 model series. The default is the maximum dimensions for each model. For skillsets created using earlier REST API versions dating back to the 2023-10-01-preview, dimensions are fixed at 1536. When setting the dimensions property on a skill, make sure to set the `dimensions` property on the [vector field definition](vector-search-how-to-create-index.md#add-a-vector-field-to-the-fields-collection) to the same value. |
+| `modelName` | Required. Set this property to the deployment name of an Azure OpenAI embedding model deployed on the provider specified through `resourceUri` and identified through `deploymentId`. Currently, the supported values are `text-embedding-ada-002`, `text-embedding-3-large`, and `text-embedding-3-small`.  |
+| `dimensions` | Optional. The dimensions of embeddings that you would like to generate, assuming the model supports a range of dimensions. Supported ranges are listed below, and currently only apply to the text-embedding-3 model series. The default is the maximum dimensions for each model. For skillsets created using earlier REST API versions dating back to the 2023-10-01-preview, dimensions are fixed at 1536. When setting the dimensions property on a skill, make sure to set the `dimensions` property on the [vector field definition](vector-search-how-to-create-index.md#add-a-vector-field-to-the-fields-collection) to the same value. |
 
 ## Supported dimensions by `modelName`
 

@@ -33,15 +33,15 @@ Microsoft.Skills.Text.SplitSkill
 
 Parameters are case-sensitive. 
 
-| Parameter name     | Version   | Description |
+| Parameter name     | Description |
 |--------------------|-------------|-------------|
-| `textSplitMode`    | All versions | Either `pages` or `sentences`. Pages have a configurable maximum length, but the skill attempts to avoid truncating a sentence so the actual length might be smaller. Sentences are a string that terminates at sentence-ending punctuation, such as a period, question mark, or exclamation point, assuming the language has sentence-ending punctuation. | 
-| `maximumPageLength` | All versions | Only applies if `textSplitMode` is set to `pages`. For `unit` set to `characters`, this parameter refers to the maximum page length in characters as measured by `String.Length`. The minimum value is 300, the maximum is 50000, and the default value is 5000.  The algorithm does its best to break the text on sentence boundaries, so the size of each chunk might be slightly less than `maximumPageLength`. <br><br>For `unit` set to `azureOpenAITokens`, the maximum page length is the token length limit of the model. For text embedding models, a general recommendation for page length is 512 tokens. |
-| `defaultLanguageCode`	| All versions | (optional) One of the following language codes: `am, bs, cs, da, de, en, es, et, fr, he, hi, hr, hu, fi, id, is, it, ja, ko, lv, no, nl, pl, pt-PT, pt-BR, ru, sk, sl, sr, sv, tr, ur, zh-Hans`. Default is English (en). A few things to consider: <ul><li>Providing a language code is useful to avoid cutting a word in half for nonwhitespace languages such as Chinese, Japanese, and Korean.</li><li>If you don't know the language  in advance (for example, if you're using the [LanguageDetectionSkill](cognitive-search-skill-language-detection.md) to detect language), we recommend the `en` default. </li></ul>  |
-| `pageOverlapLength` | [2024-07-01](/rest/api/searchservice/skillsets/create-or-update) | Only applies if `textSplitMode` is set to `pages`. Each page starts with this number of characters or tokens from the end of the previous page. If this parameter is set to 0, there's no overlapping text on successive pages. This [example](#example-for-chunking-and-vectorization) includes the parameter. |
-| `maximumPagesToTake` | [2024-07-01](/rest/api/searchservice/skillsets/create-or-update) | Only applies if `textSplitMode` is set to `pages`. Number of pages to return. The default is 0, which means to return all pages. You should set this value if only a subset of pages are needed. This [example](#example-for-chunking-and-vectorization) includes the parameter.|
-| `unit` | [2024-09-01-preview](/rest/api/searchservice/skillsets/create-or-update?view=rest-searchservice-2024-09-01-preview&preserve-view=true) | **New**. Only applies if `textSplitMode` is set to `pages`. Specifies whether to chunk by `characters` (default) or `azureOpenAITokens`. Setting the unit affects `maximumPageLength` and `pageOverlapLength`. |
-| `azureOpenAITokenizerParameters` | [2024-09-01-preview](/rest/api/searchservice/skillsets/create-or-update?view=rest-searchservice-2024-09-01-preview&preserve-view=true) | **New**. An object providing extra parameters for the `azureOpenAITokens` unit. <br><br>`encoderModelName` is a designated tokenizer used for converting text into tokens, essential for natural language processing (NLP) tasks. Different models use different tokenizers. Valid values include cl100k_base (default) used by GPT-35-Turbo and GPT-4. Other valid values are r50k_base, p50k_base, and p50k_edit. The skill implements the tiktoken library by way of [SharpToken](https://www.nuget.org/packages/SharpToken) and `Microsoft.ML.Tokenizers` but doesn't support every encoder. For example, there's currently no support for o200k_base encoding used by GPT-4o. <br><br>`allowedSpecialTokens` defines a collection of special tokens that are permitted within the tokenization process. Special tokens are  string that you want to treat uniquely, ensuring they aren't split during tokenization. For example ["[START"], "[END]"]. If the `tiktoken` library doesn't perform tokenization as expected, either due to language-specific limitations or other unexpected behaviors, it's recommended to use text splitting instead.|
+| `textSplitMode`    | Either `pages` or `sentences`. Pages have a configurable maximum length, but the skill attempts to avoid truncating a sentence so the actual length might be smaller. Sentences are a string that terminates at sentence-ending punctuation, such as a period, question mark, or exclamation point, assuming the language has sentence-ending punctuation. | 
+| `maximumPageLength` | Only applies if `textSplitMode` is set to `pages`. For `unit` set to `characters`, this parameter refers to the maximum page length in characters as measured by `String.Length`. The minimum value is 300, the maximum is 50000, and the default value is 5000.  The algorithm does its best to break the text on sentence boundaries, so the size of each chunk might be slightly less than `maximumPageLength`. <br><br>For `unit` set to `azureOpenAITokens`, the maximum page length is the token length limit of the model. For text embedding models, a general recommendation for page length is 512 tokens. |
+| `defaultLanguageCode`	| (optional) One of the following language codes: `am, bs, cs, da, de, en, es, et, fr, he, hi, hr, hu, fi, id, is, it, ja, ko, lv, no, nl, pl, pt-PT, pt-BR, ru, sk, sl, sr, sv, tr, ur, zh-Hans`. Default is English (en). A few things to consider: <ul><li>Providing a language code is useful to avoid cutting a word in half for nonwhitespace languages such as Chinese, Japanese, and Korean.</li><li>If you don't know the language  in advance (for example, if you're using the [LanguageDetectionSkill](cognitive-search-skill-language-detection.md) to detect language), we recommend the `en` default. </li></ul>  |
+| `pageOverlapLength` | Only applies if `textSplitMode` is set to `pages`. Each page starts with this number of characters or tokens from the end of the previous page. If this parameter is set to 0, there's no overlapping text on successive pages. This [example](#example-for-chunking-and-vectorization) includes the parameter. |
+| `maximumPagesToTake` | Only applies if `textSplitMode` is set to `pages`. Number of pages to return. The default is 0, which means to return all pages. You should set this value if only a subset of pages are needed. This [example](#example-for-chunking-and-vectorization) includes the parameter.|
+| `unit` | Only applies if `textSplitMode` is set to `pages`. Specifies whether to chunk by `characters` (default) or `azureOpenAITokens`. Setting the unit affects `maximumPageLength` and `pageOverlapLength`. |
+| `azureOpenAITokenizerParameters` An object providing extra parameters for the `azureOpenAITokens` unit. <br><br>`encoderModelName` is a designated tokenizer used for converting text into tokens, essential for natural language processing (NLP) tasks. Different models use different tokenizers. Valid values include cl100k_base (default) used by GPT-35-Turbo and GPT-4. Other valid values are r50k_base, p50k_base, and p50k_edit. The skill implements the tiktoken library by way of [SharpToken](https://www.nuget.org/packages/SharpToken) and `Microsoft.ML.Tokenizers` but doesn't support every encoder. For example, there's currently no support for o200k_base encoding used by GPT-4o. <br><br>`allowedSpecialTokens` defines a collection of special tokens that are permitted within the tokenization process. Special tokens are  string that you want to treat uniquely, ensuring they aren't split during tokenization. For example ["[START"], "[END]"]. If the `tiktoken` library doesn't perform tokenization as expected, either due to language-specific limitations or other unexpected behaviors, it's recommended to use text splitting instead.|
 
 ## Skill Inputs
 

@@ -105,7 +105,7 @@ The following example shows a hybrid query request using the REST API.
 This example is from the [vector quickstart](https://raw.githubusercontent.com/Azure-Samples/azure-search-rest-samples/refs/heads/main/Quickstart-vectors/az-search-quickstart-vectors.rest) that has vector and nonvector content, and several query examples. For brevity, the vector is truncated in this article. 
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-07-01
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -240,7 +240,7 @@ This section has multiple query examples that illustrate hybrid query patterns.
 This example adds a filter, which is applied to the `filterable` nonvector fields of the search index.
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-07-01
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -324,7 +324,7 @@ Assuming that you [have semantic ranker](semantic-how-to-enable-disable.md) and
 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.
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-07-01
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -365,7 +365,7 @@ api-key: {{admin-api-key}}
 Here's the last query in the collection. It's the same semantic hybrid query as the previous example, but with a filter.
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-07-01
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {

@@ -34,7 +34,7 @@ Hybrid search is predicated on having a search index that contains fields of var
 A representative hybrid query might be as follows (notice that the vector queries have placeholder values for brevity):
 
 ```http
-POST https://{{searchServiceName}}.search.windows.net/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01
+POST https://{{searchServiceName}}.search.windows.net/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01
   content-type: application/JSON
 {
     "count": true,

@@ -92,7 +92,7 @@ To connect to your search service:
 1. Create a `$url` object that targets the indexes collection on your search service. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
 
     ```powershell
-    $url = "<YOUR-SEARCH-SERVICE>/indexes?api-version=2024-07-01&`$select=name"
+    $url = "<YOUR-SEARCH-SERVICE>/indexes?api-version=2025-09-01&`$select=name"
     ```
 
 1. Run `Invoke-RestMethod` to send a GET request to your search service. Include `ConvertTo-Json` to view responses from the service.
@@ -152,7 +152,7 @@ To create an index:
 2. Update the `$url` object to target the new index. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
 
     ```powershell
-    $url = "<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart?api-version=2024-07-01"
+    $url = "<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart?api-version=2025-09-01"
     ```
 
 3. Run `Invoke-RestMethod` to create the index on your search service.
@@ -275,7 +275,7 @@ To upload documents to your index:
 2. Update the `$url` object to target the indexing endpoint. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
 
     ```powershell
-    $url = "<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs/index?api-version=2024-07-01"
+    $url = "<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs/index?api-version=2025-09-01"
     ```
 
 3. Run `Invoke-RestMethod` to send the upload request to your search service.
@@ -301,7 +301,7 @@ To run a full-text query against your index:
 1. Update the `$url` object to specify search parameters. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
 
     ```powershell
-    $url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2024-07-01&search=attached restaurant&searchFields=Description,Tags&$select=HotelId,HotelName,Tags,Description&$count=true'
+    $url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=attached restaurant&searchFields=Description,Tags&$select=HotelId,HotelName,Tags,Description&$count=true'
     ```
 
 2. Run `Invoke-RestMethod` to send the query request to your search service.
@@ -344,20 +344,20 @@ Run the following commands to explore the query syntax. You can perform string s
 # Query example 1
 # Search the index for the terms 'restaurant' and 'wifi'
 # Return only the HotelName, Description, and Tags fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2024-07-01&search=restaurant wifi&$count=true&$select=HotelName,Description,Tags'
+$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=restaurant wifi&$count=true&$select=HotelName,Description,Tags'
 
 # Query example 2 
 # Use a filter to find hotels rated 4 or higher
 # Return only the HotelName and Rating fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2024-07-01&search=*&$filter=Rating gt 4&$select=HotelName,Rating'
+$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=*&$filter=Rating gt 4&$select=HotelName,Rating'
 
 # Query example 3
 # Take the top two results
 # Return only the HotelName and Category fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2024-07-01&search=boutique&$top=2&$select=HotelName,Category'
+$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=boutique&$top=2&$select=HotelName,Category'
 
 # Query example 4
 # Sort by a specific field (Address/City) in ascending order
 # Return only the HotelName, Address/City, Tags, and Rating fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2024-07-01&search=pool&$orderby=Address/City asc&$select=HotelName, Address/City, Tags, Rating'
+$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=pool&$orderby=Address/City asc&$select=HotelName, Address/City, Tags, Rating'
 ```

@@ -89,7 +89,7 @@ To set up your request file:
     @token = PUT-YOUR-PERSONAL-IDENTITY-TOKEN-HERE
 
     ### List existing indexes by name
-    GET {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+    GET {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
         Authorization: Bearer {{token}}
     ```
 
@@ -111,7 +111,7 @@ To create an index:
 
     ```http
     ### Create a new index
-    POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
     
@@ -169,7 +169,7 @@ To upload documents to your index:
 
     ```http
     ### Upload documents
-    POST {{baseUrl}}/indexes/hotels-quickstart/docs/index?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-quickstart/docs/index?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
     
@@ -275,7 +275,7 @@ To run a full-text query against your index:
 
     ```http
     ### Run a query
-    POST {{baseUrl}}/indexes/hotels-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-quickstart/docs/search?api-version=2025-09-01  HTTP/1.1
       Content-Type: application/json
       Authorization: Bearer {{token}}
     

@@ -75,7 +75,7 @@ To connect using REST:
    @token = PUT-YOUR-PERSONAL-IDENTITY-TOKEN-HERE
 
    ### List existing indexes
-   GET {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+   GET {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
       Content-Type: application/json
       Authorization: Bearer {{token}}
    ```

@@ -109,7 +109,7 @@ The index schema in this example is organized around hotel content. Sample data
 
     ```http
     ### Create a new index
-    POST  {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+    POST  {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{token}}
 
@@ -402,7 +402,7 @@ In Azure AI Search, the index contains all searchable data and queries run on th
 
     ```http
     ### Upload documents
-    POST {{baseUrl}}/indexes/hotels-quickstart-vectors/docs/index?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-quickstart-vectors/docs/index?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{token}}
 
@@ -673,7 +673,7 @@ The vector query string is semantically similar to the search string, but it inc
 
     ```http
     ### Run a single vector query
-    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
         
@@ -784,7 +784,7 @@ You can add filters, but the filters are applied to the nonvector content in you
 
     ```http
     ### Run a vector query with a filter
-    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
     
@@ -847,7 +847,7 @@ You can add filters, but the filters are applied to the nonvector content in you
 
     ```http
     ### Run a vector query with a geo filter
-    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
     
@@ -917,7 +917,7 @@ Hybrid search consists of keyword queries and vector queries in a single search
 
     ```http
     ### Run a hybrid query
-    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
         
@@ -1033,7 +1033,7 @@ Here's the last query in the collection. This hybrid query adds L2 semantic rank
 
     ```http
     ### Run a hybrid query with semantic reranking
-    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         Authorization: Bearer {{token}}
 
@@ -1127,7 +1127,7 @@ If you want to keep the search service, but delete the index and documents, you
 
 ```http
 ### Delete an index
-DELETE  {{baseUrl}}/indexes/hotels-vector-quickstart?api-version=2024-07-01 HTTP/1.1
+DELETE  {{baseUrl}}/indexes/hotels-vector-quickstart?api-version=2025-09-01 HTTP/1.1
     Content-Type: application/json
     Authorization: Bearer {{token}}
 ```

@@ -97,7 +97,7 @@ Call [Create Data Source](/rest/api/searchservice/data-sources/create) to set th
 
 ```http
 ### Create a data source
-POST {{baseUrl}}/datasources?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/datasources?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -124,7 +124,7 @@ Call [Create Skillset](/rest/api/searchservice/skillsets/create) to specify whic
 
 ```http
 ### Create a skillset
-POST {{baseUrl}}/skillsets?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/skillsets?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -313,7 +313,7 @@ The largest component of an index is the fields collection, where data type and
 
 ```http
 ### Create an index
-POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -406,7 +406,7 @@ Expect this step to take several minutes to complete. Even though the data set i
 
 ```http
 ### Create and run an indexer
-POST {{baseUrl}}/indexers?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexers?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -497,7 +497,7 @@ To find out whether the indexer is still running, call [Get Indexer Status](/res
 
 ```http
 ### Get Indexer Status (wait several minutes for the indexer to complete)
-GET {{baseUrl}}/indexers/cog-search-demo-idxr/status?api-version=2024-07-01  HTTP/1.1
+GET {{baseUrl}}/indexers/cog-search-demo-idxr/status?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 ```
@@ -514,7 +514,7 @@ Now that you've created an index that contains AI-generated content, call [Searc
 
 ```http
 ### Query the index\
-POST {{baseUrl}}/indexes/cog-search-demo-idx/docs/search?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/cog-search-demo-idx/docs/search?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
   
@@ -529,7 +529,7 @@ Filters can help you narrow results to items of interest:
 
 ```http
 ### Filter by organization
-POST {{baseUrl}}/indexes/cog-search-demo-idx/docs/search?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/cog-search-demo-idx/docs/search?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
   

@@ -9,7 +9,7 @@ ms.service: azure-ai-search
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 07/25/2025
+ms.date: 09/29/2025
 ms.update-cycle: 365-days
 ---
 
@@ -31,11 +31,11 @@ You can add a scoring profile to an index by editing its JSON definition in the
 
 ## Rules for scoring profiles
 
-You can use scoring profiles in [keyword search](search-lucene-query-architecture.md), [vector search](vector-search-overview.md), [hybrid search](hybrid-search-overview.md), and [semantic search (reranking)](semantic-search-overview.md). However, scoring profiles only apply to nonvector fields, so make sure your index has text or numeric fields that can be boosted or weighted. 
+You can use scoring profiles in [keyword search](search-lucene-query-architecture.md), [vector search](vector-search-overview.md), [hybrid search](hybrid-search-overview.md), and [semantic reranking)](semantic-search-overview.md). However, scoring profiles only apply to nonvector fields, so make sure your index has text or numeric fields that can be boosted or weighted. 
 
 You can have up to 100 scoring profiles within an index (see [service Limits](search-limits-quotas-capacity.md)), but you can only specify one profile at time in any given query.
 
-You can use [semantic ranker](semantic-how-to-query-request.md) with scoring profiles. Currently in preview, you can apply a [scoring profile after semantic ranking](semantic-how-to-enable-scoring-profiles.md). Otherwise, when multiple ranking or relevance features are in play, semantic ranking is the last step. [How search scoring works](search-relevance-overview.md#diagram-of-ranking-algorithms) provides an illustration.
+You can use [semantic ranker](semantic-how-to-query-request.md) with scoring profiles and apply a [scoring profile after semantic ranking](semantic-how-to-enable-scoring-profiles.md). Otherwise, when multiple ranking or relevance features are in play, semantic ranking is the last step. [How search scoring works](search-relevance-overview.md#diagram-of-ranking-algorithms) provides an illustration.
 
 [Extra rules](#rules-for-using-functions) apply specifically to functions.
 
@@ -77,7 +77,7 @@ The following definition shows a simple profile named "geo". This example boosts
 To use this scoring profile, your query is formulated to specify `scoringProfile` parameter in the request. If you're using the REST API, queries are specified through GET and POST requests. In the following example, "currentLocation" has a delimiter of a single dash (`-`). It's followed by longitude and latitude coordinates, where longitude is a negative value.
 
 ```http
-POST /indexes/hotels/docs&api-version=2024-07-01
+POST /indexes/hotels/docs&api-version=2025-09-01
 {
     "search": "inn",
     "scoringProfile": "geo",

@@ -161,7 +161,7 @@ In a search application, client code should use a library like [jQuery UI Autoco
 API usage is illustrated in the following call to the Autocomplete REST API. There are two takeaways from this example. First, as with all queries, the operation is against the documents collection of an index and the query includes a `search` parameter, which in this case provides the partial query. Second, you must add `suggesterName` to the request. If a suggester isn't defined in the index, calls to autocomplete or suggestions fail.
 
 ```http
-POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2024-07-01
+POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2025-09-01
 {
   "search": "minecraf",
   "suggesterName": "sg"

@@ -43,7 +43,7 @@ BM25 ranking provides two parameters for tuning the relevance score calculation.
 1. Use a [Create or Update Index](/rest/api/searchservice/indexes/create) request to set BM25 parameters:
 
     ```http
-    PUT [service-name].search.windows.net/indexes/[index-name]?api-version=2024-07-01&allowIndexDowntime=true
+    PUT [service-name].search.windows.net/indexes/[index-name]?api-version=2025-09-01&allowIndexDowntime=true
     {
         "similarity": {
             "@odata.type": "#Microsoft.Azure.Search.BM25Similarity",
@@ -84,7 +84,7 @@ The following links describe the Similarity property in the Azure SDKs.
 You can also use the [REST API](/rest/api/searchservice/indexes/create). The following example creates a new index with the "similarity" property set to BM25:
 
 ```http
-PUT [service-name].search.windows.net/indexes/[index name]?api-version=2024-07-01
+PUT [service-name].search.windows.net/indexes/[index name]?api-version=2025-09-01
 {
     "name": "indexName",
     "fields": [

@@ -97,7 +97,7 @@ By default, the score of a document is calculated based on statistical propertie
 If you prefer to compute the score based on the statistical properties across all shards, you can do so by adding `scoringStatistics=global` as a [query parameter](/rest/api/searchservice/documents/search-post) (or add `"scoringStatistics": "global"` as a body parameter of the [query request](/rest/api/searchservice/documents/search-post)).
 
 ```http
-POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-version=2025-09-01
 {
     "search": "<query string>",
     "scoringStatistics": "global"
@@ -107,7 +107,7 @@ POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-ve
 Using `scoringStatistics` will ensure that all shards in the same replica provide the same results. That said, different replicas can be slightly different from one another as they're always getting updated with the latest changes to your index. In some scenarios, you might want your users to get more consistent results during a "query session". In such scenarios, you can provide a `sessionId` as part of your queries. The `sessionId` is a unique string that you create to refer to a unique user session.
 
 ```http
-POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-version=2025-09-01
 {
     "search": "<query string>",
     "sessionId": "<string>"

@@ -92,7 +92,7 @@ A valid API key establishes trust, on a per request basis, between the applicati
 
     ```http
     ### Create a new index
-    POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         api-key: {{apiKey}}
     
@@ -124,7 +124,7 @@ A valid API key establishes trust, on a per request basis, between the applicati
 
     ```http
     ### Create a data source
-    POST {{baseUrl}}/datasources?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/datasources?api-version=2025-09-01  HTTP/1.1
       Content-Type: application/json
       api-key: {{apiKey}}
     
@@ -155,7 +155,7 @@ A skillset defines enrichments (skills) and your knowledge store. [Create Skills
 
     ```http
     ### Create a skillset
-    POST {{baseUrl}}/skillsets?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/skillsets?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         api-key: {{apiKey}}
     
@@ -322,7 +322,7 @@ A skillset defines enrichments (skills) and your knowledge store. [Create Skills
 
     ```http
     ### Create indexer
-    POST {{baseUrl}}/indexers?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexers?api-version=2025-09-01  HTTP/1.1
         Content-Type: application/json
         api-key: {{apiKey}}
     
@@ -370,7 +370,7 @@ After you send each request, the search service should respond with a 201 succes
 
 ```http
 ### Get Indexer Status (wait several minutes for the indexer to complete)
-GET {{baseUrl}}/indexers/hotel-reviews-kstore-idxr/status?api-version=2024-07-01  HTTP/1.1
+GET {{baseUrl}}/indexers/hotel-reviews-kstore-idxr/status?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 ```
@@ -379,7 +379,7 @@ After several minutes, you can query the index to inspect the content. Even if y
 
 ```http
 ### Query the index (indexer status must be "success" before querying the index)
-POST {{baseUrl}}/indexes/hotel-reviews-kstore-idxr/docs/search?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/hotel-reviews-kstore-idxr/docs/search?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
   

@@ -160,7 +160,7 @@ The following example illustrates a resource log that includes common properties
 | Resource | String | Resource ID. For example: `/subscriptions/<your-subscription-id>/resourceGroups/<your-resource-group-name>/providers/Microsoft.Search/searchServices/<your-search-service-name>` |
 | Category | String | "OperationLogs". This value is a constant. OperationLogs is the only category used for resource logs. |
 | OperationName | String |  The name of the operation (see the [full list of operations](#resource-log-search-ops)). An example is `Query.Search` |
-| OperationVersion | String | The api-version used on the request. For example: `2024-07-01` |
+| OperationVersion | String | The api-version used on the request. For example: `2025-09-01` |
 | ResultType | String |"Success". Other possible values: Success or Failure |
 | ResultSignature | Int | An HTTP result code. For example: `200` |
 | DurationMS | Int | Duration of the operation in milliseconds. |
@@ -177,7 +177,7 @@ The following properties are specific to Azure AI Search.
 | Description_s | String | The operation's endpoint. For example: `GET /indexes('content')/docs` |
 | Documents_d | Int | Number of documents processed. |
 | IndexName_s | String | Name of the index associated with the operation. |
-| Query_s | String | The query parameters used in the request. For example: `?search=beach access&$count=true&api-version=2024-07-01` |
+| Query_s | String | The query parameters used in the request. For example: `?search=beach access&$count=true&api-version=2025-09-01` |
 
 <a name="resource-log-search-ops"></a>
 

@@ -24,7 +24,7 @@ To use full Lucene syntax, set the queryType to `full` and pass in a query expre
 The following example is a search request constructed using the full syntax. This particular example shows in-field search and term boosting. It looks for hotels where the category field contains the term `budget`. Any documents containing the phrase `"recently renovated"` are ranked higher as a result of the term boost value (3).  
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
   "queryType": "full",
   "search": "category:budget AND \"recently renovated\"^3",

@@ -28,7 +28,7 @@ Although the simple parser is based on the [Apache Lucene Simple Query Parser](h
 This example shows a simple query, distinguished by `"queryType": "simple"` and valid syntax. Although query type is set below, it's the default and can be omitted unless you're reverting from an alternative type. The following example is a search over independent terms, with a requirement that all matching documents include "pool".
 
 ```http
-POST https://{{service-name}}.search.windows.net/indexes/hotel-rooms-sample/docs/search?api-version=2024-07-01
+POST https://{{service-name}}.search.windows.net/indexes/hotel-rooms-sample/docs/search?api-version=2025-09-01
 {
   "queryType": "simple",
   "search": "budget hotel +pool",

@@ -32,7 +32,7 @@ The remainder of this article is focused on queries and client code. It uses Jav
 Elements of a request include one of the search-as-you-type APIs, a partial query, and a suggester. The following script illustrates components of a request, using the Autocomplete REST API as an example.
 
 ```http
-POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2024-07-01
+POST /indexes/myxboxgames/docs/autocomplete?search&api-version=2025-09-01
 {
   "search": "minecraf",
   "suggesterName": "sg"

@@ -98,7 +98,7 @@ You can control which blobs are indexed, and which are skipped, by the blob's fi
 Include specific file extensions by setting `"indexedFileNameExtensions"` to a comma-separated list of file extensions (with a leading dot). Exclude specific file extensions by setting `"excludedFileNameExtensions"` to the extensions that should be skipped. If the same extension is in both lists, it's excluded from indexing.
 
 ```http
-PUT /indexers/[indexer name]?api-version=2024-07-01
+PUT /indexers/[indexer name]?api-version=2025-09-01
 {
     "parameters" : { 
         "configuration" : { 

@@ -158,7 +158,7 @@ sections:
           
           * Add a "vectorSearch" section to the index schema specifying the configuration used by vector search fields, including the parameters of the Approximate Nearest Neighbor algorithm used, like HNSW.
           
-          * Use the latest stable version, [**2024-07-01**](/rest/api/searchservice), or an Azure SDK to create or update the index, load documents, and issue queries. For more information, see [Create a vector index](vector-search-how-to-create-index.md).
+          * Use the latest stable version, [**2025-09-01**](/rest/api/searchservice), or an Azure SDK to create or update the index, load documents, and issue queries. For more information, see [Create a vector index](vector-search-how-to-create-index.md).
 
   - name: Queries
     questions:

@@ -109,7 +109,7 @@ In the [search index](search-what-is-an-index.md), add fields to accept the cont
 1. [Create or update an index](/rest/api/searchservice/indexes/create-or-update) to define search fields that will store file content and metadata.
 
     ```http
-    POST /indexes?api-version=2024-07-01
+    POST /indexes?api-version=2025-09-01
     {
       "name" : "my-search-index",
       "fields": [
@@ -150,7 +150,7 @@ Once the index and data source have been created, you're ready to create the ind
 1. [Create or update an indexer](/rest/api/searchservice/indexers/create-or-update) by giving it a name and referencing the data source and target index:
 
     ```http
-    POST /indexers?api-version=2024-07-01
+    POST /indexers?api-version=2025-09-01
     {
       "name" : "my-file-indexer",
       "dataSourceName" : "my-file-datasource",
@@ -186,7 +186,7 @@ An indexer runs automatically when it's created. You can prevent this by setting
 To monitor the indexer status and execution history, send a [Get Indexer Status](/rest/api/searchservice/indexers/get-status) request:
 
 ```http
-GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
+GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2025-09-01
   Content-Type: application/json  
   api-key: [admin key]
 ```

@@ -57,7 +57,7 @@ One of the limits on a filter expression is the maximum size limit of the reques
 The following examples represent prototypical filter definitions in several APIs.
 
 ```http
-POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/hotels/docs/search?api-version=2025-09-01
 {
     "search": "*",
     "filter": "Rooms/any(room: room/BaseRate lt 150.0)",

@@ -149,7 +149,7 @@ Choose a tab for the various API syntax. There's currently no portal support for
 
 Index projections are generally available. We recommend the most recent stable API:
 
-- [Create Skillset (api-version=2024-07-01)](/rest/api/searchservice/skillsets/create)
+- [Create Skillset (api-version=2025-09-01)](/rest/api/searchservice/skillsets/create)
 
 Here's an example payload for an index projections definition that you might use to project individual pages output by the [Text Split skill](cognitive-search-skill-textsplit.md) as their own documents in the search index.
 

@@ -73,7 +73,7 @@ Putting it all together, here are the complete payload examples.
 Datasource: 
 
 ```http
-POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 {
@@ -87,7 +87,7 @@ api-key: [admin key]
 Indexer:
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 {

@@ -159,7 +159,7 @@ The data source definition specifies the data to index, credentials, and policie
 1. [Create Data Source](/rest/api/searchservice/data-sources/create) or [Create or Update Data Source](/rest/api/searchservice/data-sources/create-or-update) to set its definition: 
 
    ```http
-    POST https://myservice.search.windows.net/datasources?api-version=2024-07-01
+    POST https://myservice.search.windows.net/datasources?api-version=2025-09-01
     Content-Type: application/json
     api-key: admin-key
 
@@ -201,7 +201,7 @@ In a [search index](search-what-is-an-index.md), add fields that correspond to t
 1. [Create or update an index](/rest/api/searchservice/indexes/create) to define search fields that store data:
 
     ```http
-    POST https://[service name].search.windows.net/indexes?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexes?api-version=2025-09-01
     Content-Type: application/json
     api-key: [Search service admin key]
     {
@@ -254,7 +254,7 @@ Once the index and data source have been created, you're ready to create the ind
 1. [Create or update an indexer](/rest/api/searchservice/indexers/create) by giving it a name and referencing the data source and target index:
 
     ```http
-    POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
     Content-Type: application/json
     api-key: [search service admin key]
     {
@@ -310,7 +310,7 @@ To monitor the indexer status and execution history, check the indexer execution
 ### [**REST**](#tab/rest-check-indexer)
 
 ```http
-GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
+GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2025-09-01
   Content-Type: application/json  
   api-key: [admin key]
 ```
@@ -384,7 +384,7 @@ Database requirements:
 Change detection policies are added to data source definitions. To use this policy, edit the data source definition in the Azure portal, or use REST to update your data source like this:
 
 ```http
-POST https://myservice.search.windows.net/datasources?api-version=2024-07-01
+POST https://myservice.search.windows.net/datasources?api-version=2025-09-01
 Content-Type: application/json
 api-key: admin-key
     {
@@ -422,7 +422,7 @@ The high water mark column must meet the following requirements:
 Change detection policies are added to data source definitions. To use this policy, create or update your data source like this:
 
 ```http
-POST https://myservice.search.windows.net/datasources?api-version=2024-07-01
+POST https://myservice.search.windows.net/datasources?api-version=2025-09-01
 Content-Type: application/json
 api-key: admin-key
     {

@@ -332,7 +332,7 @@ In this section, you specify the connection information for your Azure AI Search
 
    ```HTTP
    ### List existing indexes by name
-   GET {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+   GET {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
      Content-Type: application/json
      Authorization: Bearer {{token}}
    ```
@@ -379,7 +379,7 @@ In this section, you connect to a [supported data source](#supported-data-source
 
    ```HTTP
    ### Create a data source
-   POST {{baseUrl}}/datasources?api-version=2024-07-01  HTTP/1.1
+   POST {{baseUrl}}/datasources?api-version=2025-09-01  HTTP/1.1
      Content-Type: application/json
      Authorization: Bearer {{token}}
 
@@ -454,7 +454,7 @@ For built-in data chunking, Azure AI Search offers the [Text Split skill](cognit
 
    ```HTTP
    ### Create a skillset
-   POST {{baseUrl}}/skillsets?api-version=2024-07-01  HTTP/1.1
+   POST {{baseUrl}}/skillsets?api-version=2025-09-01  HTTP/1.1
      Content-Type: application/json
      Authorization: Bearer {{token}}
 
@@ -632,7 +632,7 @@ In addition to vector fields, the sample index in the following steps contains n
 
    ```HTTP
    ### Create a vector index
-   POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+   POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
      Content-Type: application/json
      Authorization: Bearer {{token}}
 
@@ -810,7 +810,7 @@ In this section, you create an [indexer](search-indexer-overview.md) to drive th
 
    ```HTTP
    ### Create an indexer
-   POST {{baseUrl}}/indexers?api-version=2024-07-01  HTTP/1.1
+   POST {{baseUrl}}/indexers?api-version=2025-09-01  HTTP/1.1
      Content-Type: application/json
      Authorization: Bearer {{token}}
 
@@ -847,7 +847,7 @@ In this section, you verify that your content was successfully indexed by [creat
 
    ```HTTP
    ### Run a vector query
-   POST {{baseUrl}}/indexes('my-vector-index')/docs/search.post.search?api-version=2024-07-01  HTTP/1.1
+   POST {{baseUrl}}/indexes('my-vector-index')/docs/search.post.search?api-version=2025-09-01  HTTP/1.1
      Content-Type: application/json
      Authorization: Bearer {{token}}
 

@@ -57,7 +57,7 @@ In the Azure portal, use an [import wizard](search-import-data-portal.md) to cre
 1. Formulate a POST call specifying the index name, the "docs/index" endpoint, and a request body that includes the `@search.action` parameter.
 
     ```http
-    POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/index?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/index?api-version=2025-09-01
     Content-Type: application/json   
     api-key: [admin key] 
     {
@@ -95,7 +95,7 @@ In the Azure portal, use an [import wizard](search-import-data-portal.md) to cre
 1. [Look up the documents](/rest/api/searchservice/documents/get) you just added as a validation step:
 
     ```http
-    GET https://[service name].search.windows.net/indexes/hotel-sample-index/docs/1111?api-version=2024-07-01
+    GET https://[service name].search.windows.net/indexes/hotel-sample-index/docs/1111?api-version=2025-09-01
     ```
 
 When the document key or ID is new, **null** becomes the value for any field that is unspecified in the document. For actions on an existing document, updated values replace the previous values. Any fields that weren't specified in a "merge" or "mergeUpload" are left intact in the search index.

@@ -232,7 +232,7 @@ An indexer runs automatically when it's created. You can prevent this by setting
 To monitor the indexer status and execution history, send a [Get Indexer Status](/rest/api/searchservice/indexers/get-status) request:
 
 ```http
-GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
+GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2025-09-01
   Content-Type: application/json  
   api-key: [admin key]
 ```
@@ -284,7 +284,7 @@ By default, the blob indexer stops as soon as it encounters a blob with an unsup
 There are five indexer properties that control the indexer's response when errors occur. 
 
 ```http
-PUT /indexers/[indexer name]?api-version=2024-07-01
+PUT /indexers/[indexer name]?api-version=2025-09-01
 {
   "parameters" : { 
     "maxFailedItems" : 10, 

@@ -78,7 +78,7 @@ In Azure AI Search, set a native blob soft deletion detection policy on the data
 Set the soft deletion detection policy in the data source definition. Specify the API version when creating or updating the data source.
 
 ```http
-PUT https://[service name].search.windows.net/datasources/blob-datasource?api-version=2024-07-01
+PUT https://[service name].search.windows.net/datasources/blob-datasource?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 {
@@ -117,7 +117,7 @@ There are steps to follow in both Azure Storage and Azure AI Search, but there a
 1. In Azure AI Search, edit the data source definition to include a "dataDeletionDetectionPolicy" property. For example, the following policy considers a file to be deleted if it has a metadata property `IsDeleted` with the value `true`:
 
     ```http
-    PUT https://[service name].search.windows.net/datasources/file-datasource?api-version=2024-07-01
+    PUT https://[service name].search.windows.net/datasources/file-datasource?api-version=2025-09-01
     {
         "name" : "file-datasource",
         "type" : "azurefile",

@@ -104,7 +104,7 @@ The data source definition specifies the data to index, credentials, and policie
 1. [Create or update a data source](/rest/api/searchservice/data-sources/create-or-update) to set its definition: 
 
     ```http
-    POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+    POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
     Content-Type: application/json
     api-key: [Search service admin key]
     {
@@ -234,7 +234,7 @@ In a [search index](search-what-is-an-index.md), add fields to accept the source
 1. [Create or update an index](/rest/api/searchservice/indexes/create) to define search fields that store data:
 
     ```http
-    POST https://[service name].search.windows.net/indexes?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexes?api-version=2025-09-01
     Content-Type: application/json
     api-key: [Search service admin key]
     {
@@ -282,7 +282,7 @@ Once the index and data source have been created, you're ready to create the ind
 1. [Create or update an indexer](/rest/api/searchservice/indexers/create) by giving it a name and referencing the data source and target index:
 
     ```http
-    POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
     Content-Type: application/json
     api-key: [search service admin key]
     {
@@ -323,7 +323,7 @@ To monitor the indexer status and execution history, check the indexer execution
 
 ### [**REST**](#tab/rest-check-indexer)
 ```http
-GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
+GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2025-09-01
   Content-Type: application/json  
   api-key: [admin key]
 ```
@@ -427,7 +427,7 @@ The `softDeleteColumnName` must be a top-level field in the index. Using nested
 The following example creates a data source with a soft-deletion policy:
 
 ```http
-POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
 Content-Type: application/json
 api-key: [Search service admin key]
 

@@ -61,7 +61,7 @@ The blob indexer parses the JSON document into a single search document, loading
 Although the default behavior is one search document per JSON blob, setting the **`json`** parsing mode changes the internal field mappings for content, promoting fields inside `content` to actual fields in the search index. An example indexer definition for the **`json`** parsing mode might look like this:
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -100,7 +100,7 @@ Alternatively, you can use the JSON array option. This option is useful when blo
 The `parameters` property on the indexer contains parsing mode values. For a JSON array, the indexer definition should look similar to the following example.
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -159,7 +159,7 @@ If your blob contains multiple JSON entities separated by a newline, and you wan
 For JSON lines, the indexer definition should look similar to the following example.
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 

@@ -38,7 +38,7 @@ An alternative third option for breaking content into multiple parts requires ad
 To index plain text blobs, create or update an indexer definition with the `parsingMode` configuration property set to `text` on a [Create Indexer](/rest/api/searchservice/indexers/create) request:
 
 ```http
-PUT https://[service name].search.windows.net/indexers/[indexer name]?api-version=2024-07-01
+PUT https://[service name].search.windows.net/indexers/[indexer name]?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -62,7 +62,7 @@ By default, the `UTF-8` encoding is assumed. To specify a different encoding, us
 Parsing modes are specified in the indexer definition.
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 

@@ -178,7 +178,7 @@ In a [search index](search-what-is-an-index.md), add fields to accept the conten
 1. [Create or update an index](/rest/api/searchservice/indexes/create-or-update) to define search fields that will store blob content and metadata:
 
     ```http
-    POST https://[service name].search.windows.net/indexes?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexes?api-version=2025-09-01
     {
         "name" : "my-search-index",
         "fields": [
@@ -214,7 +214,7 @@ Once the index and data source have been created, you're ready to create the ind
 1. [Create or update an indexer](/rest/api/searchservice/indexers/create-or-update) by giving it a name and referencing the data source and target index:
 
     ```http
-    POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
     {
       "name" : "my-blob-indexer",
       "dataSourceName" : "my-blob-datasource",
@@ -271,7 +271,7 @@ To illustrate, let's consider an example of two indexers, pulling data from two
 First indexer definition example:
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 {
   "name" : "my-blob-indexer1",
   "dataSourceName" : "my-blob-datasource1",
@@ -294,7 +294,7 @@ POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
 Second indexer definition that runs in parallel example:
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 {
   "name" : "my-blob-indexer2",
   "dataSourceName" : "my-blob-datasource2",
@@ -320,7 +320,7 @@ POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
 To monitor the indexer status and execution history, send a [Get Indexer Status](/rest/api/searchservice/indexers/get-status) request:
 
 ```http
-GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
+GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2025-09-01
   Content-Type: application/json  
   api-key: [admin key]
 ```
@@ -372,7 +372,7 @@ By default, the blob indexer stops as soon as it encounters a blob with an unsup
 There are five indexer properties that control the indexer's response when errors occur. 
 
 ```http
-PUT /indexers/[indexer name]?api-version=2024-07-01
+PUT /indexers/[indexer name]?api-version=2025-09-01
 {
   "parameters" : { 
     "maxFailedItems" : 10, 

@@ -89,7 +89,7 @@ The data source definition specifies the source data to index, credentials, and
 1. [Create or update a data source](/rest/api/searchservice/data-sources/create-or-update) to set its definition:
 
    ```http
-    POST https://[service name].search.windows.net/datasources?api-version=2024-07-01 
+    POST https://[service name].search.windows.net/datasources?api-version=2025-09-01 
     {
         "name": "my-table-storage-ds",
         "description": null,
@@ -175,7 +175,7 @@ In a [search index](search-what-is-an-index.md), add fields to accept the conten
 1. [Create or update an index](/rest/api/searchservice/indexes/create) to define search fields that will store content from entities:
 
     ```http
-    POST https://[service name].search.windows.net/indexes?api-version=2024-07-01 
+    POST https://[service name].search.windows.net/indexes?api-version=2025-09-01 
     {
       "name" : "my-search-index",
       "fields": [
@@ -215,7 +215,7 @@ Once you have an index and data source, you're ready to create the indexer. Inde
 1. [Create or update an indexer](/rest/api/searchservice/indexers/create) by giving it a name and referencing the data source and target index:
 
     ```http
-    POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
     {
         "name" : "my-table-indexer",
         "dataSourceName" : "my-table-storage-ds",
@@ -264,7 +264,7 @@ To monitor the indexer status and execution history, check the indexer execution
 ### [**REST**](#tab/rest-check-indexer)
 
 ```http
-GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2024-07-01
+GET https://myservice.search.windows.net/indexers/myindexer/status?api-version=2025-09-01
   Content-Type: application/json  
   api-key: [admin key]
 ```

@@ -105,7 +105,7 @@ When you're connecting with a system-assigned managed identity, the only change
 Here's an example using the [Create Data Source](/rest/api/searchservice/data-sources/create) REST API that exercises the _modern_ approach.
 
 ```http
-POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
 {
     "name": "my-cosmosdb-ds",
     "type": "cosmosdb",

@@ -100,7 +100,7 @@ When you're connecting with a system-assigned managed identity, the only change
 Here's an example of how to create a data source to index data from a storage account using the [Create Data Source](/rest/api/searchservice/data-sources/create) REST API and a managed identity connection string. The managed identity connection string format is the same for the REST API, .NET SDK, and the Azure portal.
 
 ```http
-POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -154,7 +154,7 @@ The index specifies the fields in a document, attributes, and other constructs t
 Here's a [Create Index](/rest/api/searchservice/indexes/create) REST API call with a searchable `booktitle` field:   
 
 ```http
-POST https://[service name].search.windows.net/indexes?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -174,7 +174,7 @@ An indexer connects a data source with a target search index, and provides a sch
 Here's a [Create Indexer](/rest/api/searchservice/indexers/create) REST API call with an Azure SQL indexer definition. The indexer runs when you submit the request.
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 

@@ -74,7 +74,7 @@ For connections made using a system-assigned managed identity, the only change t
 Provide a connection string that contains a `ResourceId`, with no account key or password. The `ResourceId` must include the subscription ID of the storage account, the resource group of the storage account, and the storage account name.
 
 ```http
-POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
 
 {
     "name" : "blob-datasource",

@@ -74,7 +74,7 @@ A connector in Power Apps is a data source connection. In this step, create a cu
    * For the URL, enter a sample query for your search index (`search=*` returns all documents, `$select=` lets you choose fields). The API version is required. Fully specified, a URL might look like the following example. Notice that the `https://` prefix is omitted.
 
      ```http
-     mydemo.search.windows.net/indexes/hotels-sample-index/docs?search=*&$select=HotelName,Description,Address/City&api-version=2024-07-01
+     mydemo.search.windows.net/indexes/hotels-sample-index/docs?search=*&$select=HotelName,Description,Address/City&api-version=2025-09-01
      ```
 
    * For Headers, type `Content-Type application/json`.
@@ -95,7 +95,7 @@ A connector in Power Apps is a data source connection. In this step, create a cu
 
     :::image type="content" source="./media/search-howto-powerapps/1-10-4-parameter-metadata-select.png" alt-text="Select parameter metadata" border="true":::
 
-1. For *api-version*: Set `2024-07-01` as the **default value**, set **required** to *True*, and set **visibility** as *internal*.  
+1. For *api-version*: Set `2025-09-01` as the **default value**, set **required** to *True*, and set **visibility** as *internal*.  
 
     :::image type="content" source="./media/search-howto-powerapps/1-10-2-parameter-metadata-version.png" alt-text="Version parameter metadata" border="true":::
 
@@ -107,7 +107,7 @@ A connector in Power Apps is a data source connection. In this step, create a cu
     parameters:
       - {name: search, in: query, required: false, type: string, default: '*'}
       - {name: $select, in: query, required: false, type: string, default: 'HotelName,Description,Address/City'}
-      - {name: api-version, in: query, required: true, type: string, default: '2024-07-01',
+      - {name: api-version, in: query, required: true, type: string, default: '2025-09-01',
         x-ms-visibility: internal}
       - {name: Content-Type, in: header, required: false, type: string}
     ```

@@ -161,12 +161,12 @@ Here's a [REST API example](search-get-started-text.md) demonstrating these tips
 
 ```rest
 ### Get Stay-Kay City Hotel by ID
-GET  {{baseUrl}}/indexes/hotels-vector-quickstart/docs('1')?api-version=2024-07-01  HTTP/1.1
+GET  {{baseUrl}}/indexes/hotels-vector-quickstart/docs('1')?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     api-key: {{apiKey}}
 
 ### Change the description, city, and tags for Stay-Kay City Hotel
-POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search.index?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search.index?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -185,7 +185,7 @@ POST {{baseUrl}}/indexes/hotels-vector-quickstart/docs/search.index?api-version=
     }
        
 ### Retrieve the same document, confirm the overwrites and retention of all other values
-GET  {{baseUrl}}/indexes/hotels-vector-quickstart/docs('1')?api-version=2024-07-01  HTTP/1.1
+GET  {{baseUrl}}/indexes/hotels-vector-quickstart/docs('1')?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     api-key: {{apiKey}}
 ```
@@ -329,17 +329,17 @@ Deleting a document doesn't immediately free up space in the index. Every few mi
 1. [Look up the document](/rest/api/searchservice/documents/get) to verify the value of the document ID and to review its content before deleting it. Specify the key or document ID in the request. The following examples illustrate a simple string for the [Hotels sample index](search-get-started-portal.md) and a base-64 encoded string for the metadata_storage_path key of the [cog-search-demo index](tutorial-skillset.md).
 
     ```http
-    GET https://[service name].search.windows.net/indexes/hotel-sample-index/docs/1111?api-version=2024-07-01
+    GET https://[service name].search.windows.net/indexes/hotel-sample-index/docs/1111?api-version=2025-09-01
     ```
 
     ```http
-    GET https://[service name].search.windows.net/indexes/cog-search-demo/docs/aHR0cHM6Ly9oZWlkaWJsb2JzdG9yYWdlMi5ibG9iLmNvcmUud2luZG93cy5uZXQvY29nLXNlYXJjaC1kZW1vL2d1dGhyaWUuanBn0?api-version=2024-07-01
+    GET https://[service name].search.windows.net/indexes/cog-search-demo/docs/aHR0cHM6Ly9oZWlkaWJsb2JzdG9yYWdlMi5ibG9iLmNvcmUud2luZG93cy5uZXQvY29nLXNlYXJjaC1kZW1vL2d1dGhyaWUuanBn0?api-version=2025-09-01
     ```
 
 1. [Delete the document](/rest/api/searchservice/documents) using a delete `@search.action` to remove it from the search index.
 
     ```http
-    POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/index?api-version=2024-07-01
+    POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/index?api-version=2025-09-01
     Content-Type: application/json   
     api-key: [admin key] 
     {  

@@ -71,7 +71,7 @@ Switch to the **Indexer Definition (JSON)** tab at the top of the index to view
 1. Set the schedule property in the body of the request:
 
     ```http
-    PUT /indexers/<indexer-name>?api-version=2024-07-01
+    PUT /indexers/<indexer-name>?api-version=2025-09-01
     {
         "dataSourceName" : "myazuresqldatasource",
         "targetIndexName" : "my-target-index-name",

@@ -101,7 +101,7 @@ When you're connecting with a system-assigned managed identity, the only change
 Here's an example of how to create a data source to index data from a storage account using the [Create Data Source](/rest/api/searchservice/data-sources/create) REST API and a managed identity connection string. The managed identity connection string format is the same for the REST API, .NET SDK, and the Azure portal.  
 
 ```http
-POST https://[service name].search.windows.net/datasources?api-version=2024-07-01
+POST https://[service name].search.windows.net/datasources?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -124,7 +124,7 @@ The index specifies the fields in a document, attributes, and other constructs t
 Here's a [Create Index](/rest/api/searchservice/indexes/create) REST API call with a searchable `booktitle` field:
 
 ```http
-POST https://[service name].search.windows.net/indexes?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -144,7 +144,7 @@ An indexer connects a data source with a target search index, and provides a sch
 Here's a [Create Indexer](/rest/api/searchservice/indexers/create) REST API call with an Azure SQL indexer definition. The indexer runs when you submit the request.
 
 ```http
-POST https://[service name].search.windows.net/indexers?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexers?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 

@@ -177,7 +177,7 @@ Only URL-safe characters can appear in an Azure AI Search document key (so that
 The following example specifies the base64Encode function on `metadata_storage_name` to handle unsupported characters.
 
 ```http
-PUT /indexers?api-version=2024-07-01
+PUT /indexers?api-version=2025-09-01
 {
   "dataSourceName" : "my-blob-datasource ",
   "targetIndexName" : "my-search-index",
@@ -201,7 +201,7 @@ A document key (both before and after conversion) can't be longer than 1,024 cha
 There are times when you need to use an encoded version of a field like `metadata_storage_path` as the key, but also need an unencoded version for full text search. To support both scenarios, you can map `metadata_storage_path` to two fields: one for the key (encoded), and a second for a path field that we can assume is attributed as `searchable` in the index schema.
 
 ```http
-PUT /indexers/blob-indexer?api-version=2024-07-01
+PUT /indexers/blob-indexer?api-version=2025-09-01
 {
     "dataSourceName" : " blob-datasource ",
     "targetIndexName" : "my-target-index",

@@ -133,7 +133,7 @@ This article assumes a [REST client](search-get-started-text.md) and uses the RE
     Provide the connection string that you copied earlier with an Initial Catalog set to your database name.
 
     ```http
-    POST https://myservice.search.windows.net/datasources?api-version=2024-07-01
+    POST https://myservice.search.windows.net/datasources?api-version=2025-09-01
      Content-Type: application/json
      api-key: admin-key
      {
@@ -158,7 +158,7 @@ This article assumes a [REST client](search-get-started-text.md) and uses the RE
    [Indexer execution](search-howto-run-reset-indexers.md#indexer-execution-environment) occurs in either a private execution environment that's specific to your search service, or a multitenant environment hosted by Microsoft and used to offload expensive skillset processing for multiple customers. **When connecting over a private endpoint, indexer execution must be private.**
 
    ```http
-    POST https://myservice.search.windows.net/indexers?api-version=2024-07-01
+    POST https://myservice.search.windows.net/indexers?api-version=2025-09-01
      Content-Type: application/json
      api-key: admin-key
        {

@@ -346,7 +346,7 @@ On the Azure AI Search side, you can confirm request approval by revisiting the
 Alternatively, you can also obtain connection state by using the [Shared Private Link Resources - Get](/rest/api/searchmanagement/shared-private-link-resources/get).
 
 ```dotnetcli
-az rest --method get --uri https://management.azure.com/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/contoso/providers/Microsoft.Search/searchServices/contoso-search/sharedPrivateLinkResources/blob-pe?api-version=2024-07-01
+az rest --method get --uri https://management.azure.com/subscriptions/aaaa0a0a-bb1b-cc2c-dd3d-eeeeee4e4e4e/resourceGroups/contoso/providers/Microsoft.Search/searchServices/contoso-search/sharedPrivateLinkResources/blob-pe?api-version=2025-09-01
 ```
 
 This would return a JSON, where the connection state shows up as "status" under the "properties" section. Following is an example for a storage account.

@@ -180,7 +180,7 @@ If you're indexing content from Azure Blob Storage, and the container includes b
 In this situation, you can [set configuration options](search-howto-indexing-azure-blob-storage.md#DealingWithErrors) to allow indexer processing to continue if there are problems with individual documents.
 
 ```http
-PUT https://[service name].search.windows.net/indexers/[indexer name]?api-version=2024-07-01
+PUT https://[service name].search.windows.net/indexers/[indexer name]?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 
@@ -212,7 +212,7 @@ The blob indexer [finds and extracts text from blobs in a container](search-howt
 
 
 ```http
-PUT https://[service name].search.windows.net/indexers/[indexer name]?api-version=2024-07-01
+PUT https://[service name].search.windows.net/indexers/[indexer name]?api-version=2025-09-01
 Content-Type: application/json
 api-key: [admin key]
 

@@ -114,7 +114,7 @@ By default, a search returns all fields that are marked as retrievable. As such,
 #### Example in REST
 
 ```http
-POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "animaux acceptés",
     "searchFields": "Tags, Description_fr",
@@ -167,7 +167,7 @@ Sometimes the language of the agent issuing a query isn't known, in which case t
 You would then include the scoring profile in the search request:
 
 ```http
-POST /indexes/hotels/docs/search?api-version=2024-07-01
+POST /indexes/hotels/docs/search?api-version=2025-09-01
 {
   "search": "pets allowed",
   "searchFields": "Tags, Description_fr",

@@ -51,7 +51,7 @@ A search request is a complete specification of what should be returned in a res
 The following example is a search request you might send to Azure AI Search using the [REST API](/rest/api/searchservice/documents/search-post):
 
 ```
-POST /indexes/hotels/docs/search?api-version=2024-07-01
+POST /indexes/hotels/docs/search?api-version=2025-09-01
 {
     "search": "Spacious, air-condition* +\"Ocean view\"",
     "searchFields": "description, title",

@@ -69,7 +69,7 @@ You can also configure the graph to see the number of skill invocations over the
 You can retrieve the status and execution history of an indexer using the [Get Indexer Status command](/rest/api/searchservice/indexers/get-status):
 
 ```http
-GET https://[service name].search.windows.net/indexers/[indexer name]/status?api-version=2024-07-01
+GET https://[service name].search.windows.net/indexers/[indexer name]/status?api-version=2025-09-01
 api-key: [Search service admin key]
 ```
 

@@ -87,11 +87,11 @@ When you enable resource logging, the system captures query requests in the **Az
       AzureDiagnostics
    | project OperationName, Query_s, IndexName_s, Documents_d
    | where OperationName == "Query.Search"
-   | where Query_s != "?api-version=2024-07-01&search=*"
+   | where Query_s != "?api-version=2025-09-01&search=*"
    | where IndexName_s != "hotels-sample-index"
    ```
 
-1. Optionally, set a Column filter on *Query_s* to search over a specific syntax or string. For example, you could filter over *is equal to* `?api-version=2024-07-01&search=*&%24filter=HotelName`.
+1. Optionally, set a Column filter on *Query_s* to search over a specific syntax or string. For example, you could filter over *is equal to* `?api-version=2025-09-01&search=*&%24filter=HotelName`.
 
    ![Logged query strings](./media/search-monitor-usage/log-query-strings.png "Logged query strings")
 

@@ -47,7 +47,7 @@ You can choose which fields are in search results. While a search document might
 Pick fields that offer contrast and differentiation among documents, providing sufficient information to invite a clickthrough response on the part of the user. On an e-commerce site, it might be a product name, description, brand, color, size, price, and rating. For the built-in hotels-sample index, it might be the "select" fields in the following example:
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01 
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01 
     {  
       "search": "sandy beaches",
       "select": "HotelId, HotelName, Description, Rating, Address/City",
@@ -85,7 +85,7 @@ Azure AI Search uses server-side paging to prevent queries from retrieving too m
 The default page size is 50, while the maximum page size is 1,000. If you specify a value greater than 1,000 and there are more than 1,000 results found in your index, only the first 1,000 results are returned. If the number of matches exceed the page size, the response includes information to retrieve the next page of results. For example:
 
 ```json
-"@odata.nextLink": "https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2024-07-01"
+"@odata.nextLink": "https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2025-09-01"
 ```
 
 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).
@@ -95,7 +95,7 @@ Set `top` to override the default of 50. In newer preview APIs, if you're using
 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.
 
 ```http
-POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2024-07-01
+POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2025-09-01
 
 {
     "search": "condos with a view",
@@ -108,7 +108,7 @@ POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-samp
 This query returns the second set, skipping the first 15 to get the next 15 (16 through 30):
 
 ```http
-POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2024-07-01
+POST https://contoso-search-eastus.search.windows.net/indexes/realestate-us-sample-index/docs/search?api-version=2025-09-01
 
 {
     "search": "condos with a view",
@@ -154,7 +154,7 @@ In this workaround, sort and filter are applied to a document ID field or anothe
 1. Issue a query to return a full page of sorted results.
 
     ```http
-    POST /indexes/good-books/docs/search?api-version=2024-07-01
+    POST /indexes/good-books/docs/search?api-version=2025-09-01
         {  
           "search": "divine secrets",
           "top": 50,
@@ -173,7 +173,7 @@ In this workaround, sort and filter are applied to a document ID field or anothe
 1. Use that ID value in a range query to fetch the next page of results. This ID field should have unique values, otherwise pagination might include duplicate results.
 
     ```http
-    POST /indexes/good-books/docs/search?api-version=2024-07-01
+    POST /indexes/good-books/docs/search?api-version=2025-09-01
         {  
           "search": "divine secrets",
           "top": 50,
@@ -251,7 +251,7 @@ To return highlighted terms, include the highlight parameter in the query reques
 By default, the format mark up is `<em>`, but you can override the tag using `highlightPreTag` and `highlightPostTag` parameters. Your client code handles the response (for example, applying a bold font or a yellow background).
 
 ```http
-POST /indexes/good-books/docs/search?api-version=2024-07-01
+POST /indexes/good-books/docs/search?api-version=2025-09-01
     {  
       "search": "divine secrets",  
       "highlight": "title, original_title",
@@ -324,7 +324,7 @@ Within a highlighted field, formatting is applied to whole terms. For example, o
 Whole-term formatting applies even on a phrase search, where multiple terms are enclosed in double quotation marks. The following example is the same query, except that "divine secrets" is submitted as a quotation-enclosed phrase (some REST clients require that you escape the interior quotation marks with a backslash `\"`):
 
 ```http
-POST /indexes/good-books/docs/search?api-version=2024-07-01 
+POST /indexes/good-books/docs/search?api-version=2025-09-01 
     {  
       "search": "\"divine secrets\"",
       "select": "title,original_title",

@@ -32,7 +32,7 @@ A full text query is specified in a `search` parameter and consists of terms, qu
 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
+POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "NY +view",
     "queryType": "simple",
@@ -105,7 +105,7 @@ Use a REST client to set up a request. If you need help with getting started, se
 The following example calls the REST API for full text search:
 
 ```http
-POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "NY +view",
     "queryType": "simple",

@@ -60,7 +60,7 @@ Fuzzy queries are constructed using the full Lucene query syntax, invoking the [
 Here's an example of a query request that invokes fuzzy search. It includes four terms, two of which are misspelled:
 
 ```http
-POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "seatle~ waterfront~ view~ hotle~",
     "queryType": "full",

@@ -39,7 +39,7 @@ Request headers must have the following values:
 URI parameters must include your search service endpoint with the index name, docs collections, search command, and API version, similar to the following example:
 
 ```http
-https://{{service-name}}.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+https://{{service-name}}.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 ```
 
 The request body should be formed as valid JSON:
@@ -68,7 +68,7 @@ Fielded search scopes individual, embedded search expressions to a specific fiel
 When you use this query syntax, you can omit the `searchFields` parameter when the fields you want to query are in the search expression itself. If you include `searchFields` with fielded search, the `fieldName:searchExpression` always takes precedence over `searchFields`.
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "HotelName:(hotel NOT motel) AND Category:'Boutique'",
     "queryType": "full",
@@ -127,7 +127,7 @@ The field specified in `fieldName:searchExpression` must be a searchable field.
 Fuzzy search matches on terms that are similar, including misspelled words. To do a fuzzy search, append the tilde `~` symbol at the end of a single word with an optional parameter, a value between 0 and 2, that specifies the edit distance. For example, `blue~` or `blue~1` would return blue, blues, and glue.
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "Tags:conserge~",
     "queryType": "full",
@@ -191,7 +191,7 @@ Proximity search finds terms that are near each other in a document. Insert a ti
 This query searches for the terms *hotel* and  *airport* within five words of each other in a document. The quotation marks are escaped (`\"`) to preserve the phrase:
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "Description: \"hotel airport\"~5",
     "queryType": "full",
@@ -223,7 +223,7 @@ Term boosting refers to ranking a document higher if it contains the boosted ter
 In this *before* query, search for *beach access* and notice that there are six documents that match on one or both terms.
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "beach access",
     "queryType": "full",
@@ -306,7 +306,7 @@ In fact, only two documents match on *access*. The first instance is in second p
 In the *after* query, repeat the search, this time boosting results with the term *beach* over the term *access*. A human readable version of the query is `search=Description:beach^2 access`. Depending on your client, you might need to express `^2` as `%5E2`.
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "Description:beach^2 access",
     "queryType": "full",
@@ -393,7 +393,7 @@ After you boost the term *beach*, the match on Campus Commander Hotel moves down
 A regular expression search finds a match based on the contents between forward slashes `/` and lower-case strings, as documented in the [RegExp class](https://lucene.apache.org/core/6_6_1/core/org/apache/lucene/util/automaton/RegExp.html).
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "HotelName:/(Mo|Ho)tel/",
     "queryType": "full",
@@ -448,7 +448,7 @@ You can use generally recognized syntax for multiple (`*`) or single (`?`) chara
 In this query, search for hotel names that contain the prefix *sc*. You can't use a `*` or `?` symbol as the first character of a search.
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "HotelName:sc*",
     "queryType": "full",

@@ -60,7 +60,7 @@ Geospatial search uses kilometers for distance. Coordinates are specified in thi
 Here's an example of a filter for geospatial search. This filter finds other `Location` fields in the search index that have coordinates within a 300-kilometer radius of the geography point (in this example, Washington D.C.). It returns address information in the result, and includes an optional `facets` clause for self-navigation based on location.
 
 ```http
-POST https://{{searchServiceName}}.search.windows.net/indexes/hotels-vector-quickstart/docs/search?api-version=2024-07-01
+POST https://{{searchServiceName}}.search.windows.net/indexes/hotels-vector-quickstart/docs/search?api-version=2025-09-01
 {
     "count": true,
     "search": "*",

@@ -36,7 +36,7 @@ Request headers must have the following values:
 URI parameters must include your search service endpoint with the index name, docs collections, search command, and API version, similar to the following example:
 
 ```http
-https://{{service-name}}.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+https://{{service-name}}.search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 ```
 
 The request body should be formed as valid JSON:
@@ -63,7 +63,7 @@ The request body should be formed as valid JSON:
 Full text search can be any number of standalone terms or quote-enclosed phrases, with or without Boolean operators. 
 
 ```http
-POST /indexes/hotel-samples-index/docs/search?api-version=2024-07-01
+POST /indexes/hotel-samples-index/docs/search?api-version=2025-09-01
 {
     "search": "pool spa +airport",
     "searchMode": "any",
@@ -122,7 +122,7 @@ Uniform scores of *1.0* occur when there's no rank, either because the search wa
 After search results are returned, a logical next step is to provide a details page that includes more fields from the document. This example shows you how to return a single document using [Get Document](/rest/api/searchservice/documents/get) by passing in the document ID.
 
 ```http
-GET /indexes/hotels-sample-index/docs/41?api-version=2024-07-01
+GET /indexes/hotels-sample-index/docs/41?api-version=2025-09-01
 ```
 
 All documents have a unique identifier. If you're using the Azure portal, select the index from the **Indexes** tab and then look at the field definitions to determine which field is the key. In the REST API, the [GET Index](/rest/api/searchservice/indexes/get) call returns the index definition in the response body.
@@ -174,7 +174,7 @@ The response for the preceding query consists of the document whose key is *41*.
 Filters can be defined on any field marked as `filterable` in the index definition. For hotels-sample-index, filterable fields include *Category*, *Tags*, *ParkingIncluded*, *Rating*, and most *Address* fields.
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "art tours",
     "queryType": "simple",
@@ -204,7 +204,7 @@ The response for the preceding query is scoped to only those hotels categorized
 Filter expressions can include [search.ismatch and search.ismatchscoring functions](search-query-odata-full-text-search-functions.md), allowing you to build a search query within the filter. This filter expression uses a wildcard on *free* to select amenities including free wifi, free parking, and so forth.
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
   {
     "search": "",
     "filter": "search.ismatch('free*', 'Tags', 'full', 'any')",
@@ -258,7 +258,7 @@ Range filtering is supported through filters expressions for any data type. The
 The following query is a numeric range. In hotels-sample-index, the only filterable numeric field is `Rating`.
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "*",
     "filter": "Rating ge 2 and Rating lt 4",
@@ -297,7 +297,7 @@ The response for this query should look similar to the following example, trimme
 The next query is a range filter over a string field (Address/StateProvince):
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "*",
     "filter": "Address/StateProvince ge 'A*' and Address/StateProvince lt 'D*'",
@@ -360,7 +360,7 @@ The response for this query should look similar to the following example, trimme
 The hotels-sample-index includes a *Location* field with latitude and longitude coordinates. This example uses the [geo.distance function](search-query-odata-geo-spatial-functions.md#examples) that filters on documents within the circumference of a starting point, out to an arbitrary distance (in kilometers) that you provide. You can adjust the last value in the query (10) to reduce or enlarge the surface area of the query.
 
 ```http
-POST /indexes/v/docs/search?api-version=2024-07-01
+POST /indexes/v/docs/search?api-version=2025-09-01
 {
     "search": "*",
     "filter": "geo.distance(Location, geography'POINT(-122.335114 47.612839)') le 10",
@@ -419,7 +419,7 @@ The following example provides an illustration. The query looks for matches on *
 Notice that there's no space between the boolean operator (`-`) and the phrase *air conditioning*. The quotation marks are escaped (`\"`).
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "restaurant -\"air conditioning\"",
     "searchMode": "any",
@@ -479,7 +479,7 @@ By default, a search service returns the top 50 matches. To control the number o
 The following example uses a filter and sort order on the `Rating` field (Rating is both filterable and sortable) because it's easier to see the effects of paging on sorted results. In a regular full search query, the top matches are ranked and paged by `@search.score`.
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "*",
     "filter": "Rating gt 4",
@@ -495,7 +495,7 @@ The query finds 21 matching documents, but because you specified `top`, the resp
 To get the next five, skip the first batch:
 
 ```http
-POST /indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST /indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "*",
     "filter": "Rating gt 4",

@@ -58,7 +58,7 @@ Here's an example of admin API key usage on a create index request:
 
 ```http
 ### Create an index
-POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{adminApiKey}}
 
@@ -77,7 +77,7 @@ Here's an example of query API key usage on a Search Documents (GET) request:
 
 ```http
 ### Query an index
-GET /indexes/my-new-index/docs?search=*&api-version=2024-07-01&api-key={{queryApiKey}}
+GET /indexes/my-new-index/docs?search=*&api-version=2025-09-01&api-key={{queryApiKey}}
 ```
 
 > [!NOTE]  

@@ -73,28 +73,28 @@ $headers = @{
 To return a list of all search indexes, set the endpoint to the indexes collection.
 
 ```powershell
-$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/indexes?api-version=2024-07-01&$select=name'
+$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/indexes?api-version=2025-09-01&$select=name'
 Invoke-RestMethod -Uri $uri -Headers $headers | ConvertTo-Json
 ```
 
 To return a specific index definition, provide its name in the path. The encryptionKey property is at the end.
 
 ```powershell
-$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/indexes/<YOUR-INDEX-NAME>?api-version=2024-07-01'
+$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/indexes/<YOUR-INDEX-NAME>?api-version=2025-09-01'
 Invoke-RestMethod -Uri $uri -Headers $headers | ConvertTo-Json
 ```
 
 To return synonym maps, set the endpoint to the synonyms collection and then send the request.
 
 ```powershell
-$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/synonyms?api-version=2024-07-01&$select=name'
+$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/synonyms?api-version=2025-09-01&$select=name'
 Invoke-RestMethod -Uri $uri -Headers $headers | ConvertTo-Json
 ```
 
 The following example returns a specific synonym map definition, including the encryptionKey property is towards the end of the definition.
 
 ```powershell
-$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/synonyms/<YOUR-SYNONYM-MAP-NAME>?api-version=2024-07-01'
+$uri= 'https://<YOUR-SEARCH-SERVICE>.search.windows.net/synonyms/<YOUR-SYNONYM-MAP-NAME>?api-version=2025-09-01'
 Invoke-RestMethod -Uri $uri -Headers $headers | ConvertTo-Json
 ```
 

@@ -328,7 +328,7 @@ This approach assumes Visual Studio Code with a REST client extension.
 1. Paste and then send a request that uses the variables you've specified. For the "Search Index Data Reader" role, you can send a query. You can use any [supported API version](/rest/api/searchservice/search-service-api-versions).
 
    ```http
-   POST https://{{baseUrl}}/indexes/{{index-name}}/docs/search?api-version=2024-07-01 HTTP/1.1
+   POST https://{{baseUrl}}/indexes/{{index-name}}/docs/search?api-version=2025-09-01 HTTP/1.1
      Content-type: application/json
      Authorization: Bearer {{token}}
 
@@ -431,7 +431,7 @@ If you're already a Contributor or Owner of your search service, you can present
 1. Paste in and then send a request to confirm access. Here's one that queries the hotels-quickstart index
 
    ```http
-   POST https://{{baseUrl}}/indexes/{{index-name}}/docs/search?api-version=2024-07-01 HTTP/1.1
+   POST https://{{baseUrl}}/indexes/{{index-name}}/docs/search?api-version=2025-09-01 HTTP/1.1
      Content-type: application/json
      Authorization: Bearer {{token}}
 

@@ -77,7 +77,7 @@ In the search index, within the fields collection, you need one field that conta
    The following index schema satisfies the field requirements. Documents that you index on Azure AI Search should have values for all of these fields, including the "group_ids". For the document with `file_name` "secured_file_b", only users that belong to group IDs "group_id1" or "group_id2" have read access to the file.
 
    ```https
-   POST https://[search service].search.windows.net/indexes/securedfiles/docs/index?api-version=2024-07-01
+   POST https://[search service].search.windows.net/indexes/securedfiles/docs/index?api-version=2025-09-01
    {
         "name": "securedfiles",  
         "fields": [
@@ -101,7 +101,7 @@ In Azure AI Search, the approaches for loading data are:
 The following example shows a single HTTP POST request to the docs collection of your index's URL endpoint (see [Documents - Index](/rest/api/searchservice/documents/)). The body of the HTTP request is a JSON rendering of the documents to be indexed:
 
 ```http
-POST https://[search service].search.windows.net/indexes/securedfiles/docs/index?api-version=2024-07-01
+POST https://[search service].search.windows.net/indexes/securedfiles/docs/index?api-version=2025-09-01
 {
     "value": [
         {
@@ -155,7 +155,7 @@ This sample shows how to set up query using a POST request.
 Issue the HTTP POST request, specifying the filter in the request body:
 
 ```http
-POST https://[service name].search.windows.net/indexes/securedfiles/docs/search?api-version=2024-07-01
+POST https://[service name].search.windows.net/indexes/securedfiles/docs/search?api-version=2025-09-01
 
 {
    "filter":"group_ids/any(g:search.in(g, 'group_id1, group_id2'))"  

@@ -137,7 +137,7 @@ For help with the REST client, see [Quickstart: Full-text search using REST](sea
 
 ```http
 ### Create a data source
-POST {{baseUrl}}/datasources?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/datasources?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -165,7 +165,7 @@ HTTP/1.1 201 Created
 Transfer-Encoding: chunked
 Content-Type: application/json; odata.metadata=minimal; odata.streaming=true; charset=utf-8
 ETag: "0x8DC43A5FDB8448F"
-Location: https://<YOUR-SEARCH-SERVICE-NAME>.search.windows.net:443/datasources('ny-philharmonic-ds')?api-version=2024-07-01
+Location: https://<YOUR-SEARCH-SERVICE-NAME>.search.windows.net:443/datasources('ny-philharmonic-ds')?api-version=2025-09-01
 Server: Microsoft-IIS/10.0
 Strict-Transport-Security: max-age=2592000, max-age=15724800; includeSubDomains
 Preference-Applied: odata.include-annotations="*"
@@ -203,7 +203,7 @@ For nested JSON, the index fields must be identical to the source fields. Curren
 
 ```http
 ### Create an index
-POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -251,7 +251,7 @@ The indexer configuration includes the `jsonArray` parsing mode and a `documentR
 
 ```http
 ### Create and run an indexer
-POST {{baseUrl}}/indexers?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexers?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -280,7 +280,7 @@ You can start searching as soon as the first document is loaded.
 
 ```http
 ### Query the index
-POST {{baseUrl}}/indexes/ny-philharmonic-index/docs/search?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/ny-philharmonic-index/docs/search?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
   
@@ -317,15 +317,15 @@ Connection: close
   },
   "value": [
   ],
-  "@odata.nextLink": "https://<YOUR-SEARCH-SERVICE-NAME>.search.windows.net/indexes/ny-philharmonic-index/docs/search?api-version=2024-07-01"
+  "@odata.nextLink": "https://<YOUR-SEARCH-SERVICE-NAME>.search.windows.net/indexes/ny-philharmonic-index/docs/search?api-version=2025-09-01"
 }
 ```
 
 Add a `search` parameter to search on a string, a `select` parameter to limit the results to fewer fields, and a `filter` to further narrow the search.
 
 ```http
 ### Query the index
-POST {{baseUrl}}/indexes/ny-philharmonic-index/docs/search?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/ny-philharmonic-index/docs/search?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
   
@@ -350,19 +350,19 @@ Indexers can be reset to clear execution history, which allows a full rerun. The
 
 ```http
 ### Reset the indexer
-POST {{baseUrl}}/indexers/ny-philharmonic-indexer/reset?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexers/ny-philharmonic-indexer/reset?api-version=2025-09-01  HTTP/1.1
   api-key: {{apiKey}}
 ```
 
 ```http
 ### Run the indexer
-POST {{baseUrl}}/indexers/ny-philharmonic-indexer/run?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexers/ny-philharmonic-indexer/run?api-version=2025-09-01  HTTP/1.1
   api-key: {{apiKey}}
 ```
 
 ```http
 ### Check indexer status 
-GET {{baseUrl}}/indexers/ny-philharmonic-indexer/status?api-version=2024-07-01  HTTP/1.1
+GET {{baseUrl}}/indexers/ny-philharmonic-indexer/status?api-version=2025-09-01  HTTP/1.1
   api-key: {{apiKey}}
 ```
 

@@ -262,7 +262,7 @@ This particular example is searching for the word "door" (`"search": "door"`). I
 ```python
 import requests
 
-url = "https://{}.search.windows.net/indexes/{}/docs/search?api-version=2024-07-01".format(search_service, search_index)
+url = "https://{}.search.windows.net/indexes/{}/docs/search?api-version=2025-09-01".format(search_service, search_index)
 requests.post(url, json={"search": "door", "count": "true", "select": "Description, Translations"}, headers={"api-key": search_key}).json()
 ```
 

@@ -36,7 +36,7 @@ To create a synonym map, do so programmatically. the Azure portal doesn't suppor
 Use the [Create Synonym Map (REST API)](/rest/api/searchservice/synonym-maps/create) to create a synonym map.
 
 ```http
-POST /synonymmaps?api-version=2024-07-01
+POST /synonymmaps?api-version=2025-09-01
 {
     "name": "geo-synonyms",
     "format": "solr",
@@ -155,7 +155,7 @@ If the synonym map exists on the search service, it's used on the next query, wi
 Use the [Create or Update Index (REST API)](/rest/api/searchservice/indexes/create-or-update) to modify a field definition.
 
 ```http
-PUT /indexes?api-version=2024-07-01
+PUT /indexes?api-version=2025-09-01
 {
     "name":"hotels-sample-index",
     "fields":[

@@ -125,7 +125,7 @@ The following examples in this section use the [hotels-sample-index](search-get-
 If you want to set `queryType` to `semantic`, paste the following request into a web client as a template. Replace `search-service-name` with your search service name and replace `hotels-sample-index` if you have a different index name.
 
 ```http
-POST https://[search-service-name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST https://[search-service-name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
       "search": "interesting hotel with restaurant on site and cozy lobby or shared area",
       "count": true,
@@ -168,7 +168,7 @@ By using `semanticQuery`, you can explicitly apply [simple text syntax](query-si
 Adjust your request to the following JSON to use `semanticQuery`.
 
 ```http
-POST https://[search-service-name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2024-07-01
+POST https://[search-service-name].search.windows.net/indexes/hotels-sample-index/docs/search?api-version=2025-09-01
 {
     "search": "Description:breakfast",
     "semanticQuery": "interesting hotel with restaurant on site and cozy lobby or shared area",

@@ -67,7 +67,7 @@ A valid API key establishes trust, on a per-request basis, between the applicati
 
     ```http
     ### Create a new index
-    POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
       Content-Type: application/json
       api-key: {{apiKey}}
 
@@ -101,7 +101,7 @@ A valid API key establishes trust, on a per-request basis, between the applicati
 
     ```http
     ### Load documents
-    POST {{baseUrl}}/indexes/phone-numbers-index/docs/index?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes/phone-numbers-index/docs/index?api-version=2025-09-01  HTTP/1.1
       Content-Type: application/json
       api-key: {{apiKey}}
     
@@ -155,7 +155,7 @@ A valid API key establishes trust, on a per-request basis, between the applicati
 
     ```http  
     ### Search for a phone number
-    GET {{baseUrl}}/indexes/phone-numbers-index/docs/search?api-version=2024-07-01&search=(425) 555-0100  HTTP/1.1
+    GET {{baseUrl}}/indexes/phone-numbers-index/docs/search?api-version=2025-09-01&search=(425) 555-0100  HTTP/1.1
       Content-Type: application/json
       api-key: {{apiKey}}
     ```
@@ -193,7 +193,7 @@ A valid API key establishes trust, on a per-request basis, between the applicati
 
    ```http  
     ### Search for a phone number
-    GET {{baseUrl}}/indexes/phone-numbers-index/docs/search?api-version=2024-07-01&search=4255550100  HTTP/1.1
+    GET {{baseUrl}}/indexes/phone-numbers-index/docs/search?api-version=2025-09-01&search=4255550100  HTTP/1.1
       Content-Type: application/json
       api-key: {{apiKey}}
     ```
@@ -255,7 +255,7 @@ Azure AI Search provides an [Analyze API](/rest/api/searchservice/indexes/analyz
 Call the Analyze API using the following request:
 
 ```http
-POST {{baseUrl}}/indexes/phone-numbers-index/analyze?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/phone-numbers-index/analyze?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}}
 
@@ -440,15 +440,15 @@ All of the tokens in the output column exist in the index. If your query include
 
    ```http
     ### Delete the index
-    DELETE {{baseUrl}}/indexes/phone-numbers-index?api-version=2024-07-01 HTTP/1.1
+    DELETE {{baseUrl}}/indexes/phone-numbers-index?api-version=2025-09-01 HTTP/1.1
         api-key: {{apiKey}}
     ```
 
 1. Recreate the index using the new analyzer. This index schema adds a custom analyzer definition and a custom analyzer assignment on the phone number field.
 
     ```http
     ### Create a new index
-    POST {{baseUrl}}/indexes?api-version=2024-07-01  HTTP/1.1
+    POST {{baseUrl}}/indexes?api-version=2025-09-01  HTTP/1.1
       Content-Type: application/json
       api-key: {{apiKey}}
     
@@ -517,7 +517,7 @@ All of the tokens in the output column exist in the index. If your query include
 After you recreate the index, test the analyzer using the following request:
 
 ```http
-POST {{baseUrl}}/indexes/tutorial-first-analyzer/analyze?api-version=2024-07-01  HTTP/1.1
+POST {{baseUrl}}/indexes/tutorial-first-analyzer/analyze?api-version=2025-09-01  HTTP/1.1
   Content-Type: application/json
   api-key: {{apiKey}} 
 

@@ -18,7 +18,7 @@ Embeddings, or the numerical representation of heterogeneous content, are the ba
 
 This article covers all of the optimization techniques in Azure AI Search that can help you reduce vector size and query processing times.
 
-Vector optimization settings are specified in vector field definitions in a search index. Most of the features described in this article are generally available in the [2024-07-01 REST API](/rest/api/searchservice/operation-groups?view=rest-searchservice-2024-07-01&preserve-view=true) and Azure SDK packages targeting that version. The [latest preview version](/rest/api/searchservice/search-service-api-versions#preview-versions) adds support for truncated dimensions if you're using text-embedding-3-large or text-embedding-3-small for vectorization.
+Vector optimization settings are specified in vector field definitions in a search index. Most of the features described in this article are generally available in the [@search.rerankerBoostedScore REST API](/rest/api/searchservice/operation-groups?view=rest-searchservice-@search.rerankerBoostedScore&preserve-view=true) and Azure SDK packages targeting that version. The [latest preview version](/rest/api/searchservice/search-service-api-versions#preview-versions) adds support for truncated dimensions if you're using text-embedding-3-large or text-embedding-3-small for vectorization.
 
 ## Evaluate the options
 

@@ -197,7 +197,7 @@ Use a search client to send a query through a vectorizer. This example assumes V
 
    ```http
     ### Run a query
-    POST {{baseUrl}}/indexes/vector-nasa-ebook-txt/docs/search?api-version=2024-07-01 HTTP/1.1
+    POST {{baseUrl}}/indexes/vector-nasa-ebook-txt/docs/search?api-version=2025-09-01 HTTP/1.1
         Content-Type: application/json
         api-key: {{queryApiKey}}
     

@@ -237,7 +237,7 @@ Vector fields are characterized by [their data type](/rest/api/searchservice/sup
    The following example shows the fields collection:
 
     ```http
-    PUT https://my-search-service.search.windows.net/indexes/my-index?api-version=2024-07-01&allowIndexDowntime=true
+    PUT https://my-search-service.search.windows.net/indexes/my-index?api-version=2025-09-01&allowIndexDowntime=true
     Content-Type: application/json
     api-key: {{admin-api-key}}
     {

@@ -26,7 +26,7 @@ There are three steps to configuring an index for binary vectors:
 
 This article assumes you're familiar with [creating an index in Azure AI Search](search-how-to-create-search-index.md) and [adding vector fields](vector-search-how-to-create-index.md). It uses the REST APIs to illustrate each step, but you could also add a binary field to an index in the Azure portal or Azure SDK.
 
-The binary data type is generally available starting with API version 2024-07-01 and is assigned to fields using the [Create Index](/rest/api/searchservice/indexes/create) or [Create Or Update Index](/rest/api/searchservice/indexes/create-or-update) APIs.
+The binary data type is assigned to fields using the [Create Index](/rest/api/searchservice/indexes/create) or [Create Or Update Index](/rest/api/searchservice/indexes/create-or-update) APIs.
 
 > [!TIP]
 > If you're investigating binary vector support for its smaller footprint, you might also consider the vector quantization and storage reduction features in Azure AI Search. Inputs are float32 or float16 embeddings. Output is stored data in a much smaller format. For more information, see [Compress using binary or scalar quantization](vector-search-how-to-quantization.md) and [Assign narrow data types](vector-search-how-to-assign-narrow-data-types.md).
@@ -44,7 +44,7 @@ The binary data type is generally available starting with API version 2024-07-01
 
 Vector search algorithms are used to create the query navigation structures during indexing. For binary vector fields, vector comparisons are performed using the Hamming distance metric. 
 
-1. To add a binary field to an index, set up a [`Create or Update Index`](/rest/api/searchservice/indexes/create-or-update?view=rest-searchservice-2024-07-01&preserve-view=true) request using the REST API or the Azure portal.
+1. To add a binary field to an index, set up a [`Create or Update Index`](/rest/api/searchservice/indexes/create-or-update) request using the REST API or the Azure portal.
 
 1. In the index schema, add a `vectorSearch` section that specifies profiles and algorithms.
 

@@ -64,14 +64,14 @@ It's particularly effective for embeddings with dimensions greater than 1024. Fo
 
 Rescoring is an optional technique used to offset information loss due to vector quantization. During query execution, it uses oversampling to pick up extra vectors, and supplemental information to rescore initial results found by the query. Supplemental information is either uncompressed original full-precision vectors - or for binary quantization only - you have the option of rescoring using the binary quantized document candidates against the query vector. 
 
-Only HNSW graphs allow rescoring. Exhaustive KNN doesn't support rescoring because by definition, all vectors are scanned at query time, which makes oversampling irrelevant.
+Only HNSW graphs allow rescoring. Exhaustive KNN doesn't support rescoring because by definition, all vectors are scanned at query time, which makes rescoring and oversampling irrelevant.
 
 Rescoring options are specified in the index, but you can invoke rescoring at query time by adding the oversampling query parameter.
 
 | Object | Properties |
 |--------|------------|
-| Index | Add [`RescoringOptions`](/rest/api/searchservice/indexes/create-or-update#rescoringoptions) to the vector compressions section: `rescoringOptions.enableRescoring` (true or false), `rescoringOptions.defaultOversampling` (an integer), `rescoringOptions.rescoreStorageMethod` (preserveOriginals or discardOriginals). We recommend preserveOriginals for scalar quantization and discardOriginals for binary quantization. |
-| Query | Add `oversampling` on [`RawVectorQuery`](/rest/api/searchservice/documents/search-post#rawvectorquery) or [`VectorizableTextQuery`](/rest/api/searchservice/documents/search-post#vectorizabletextquery) definitions. |
+| Index | Add [`RescoringOptions`](/rest/api/searchservice/indexes/create-or-update#rescoringoptions) to the vector compressions section. The examples in this article use `RescoringOptions`. |
+| Query | Add `oversampling` on [`RawVectorQuery`](/rest/api/searchservice/documents/search-post#rawvectorquery) or [`VectorizableTextQuery`](/rest/api/searchservice/documents/search-post#vectorizabletextquery) definitions. Adding `oversampling` invokes rescoring at query time. |
 
 > [!NOTE]
 > Rescoring parameter names have changed over the last several releases. If you're using an older preview API, review the [upgrade instructions](search-api-migration.md#upgrade-to-2024-11-01-preview) for addressing breaking changes.
@@ -80,9 +80,11 @@ The generalized process for rescoring is:
 
 1. The vector query executes over compressed vector fields.
 1. The vector query returns the top k oversampled candidates.
-1. Oversampled k candidates are rescored using either the uncompressed original vectors, or the dot product of binary quantization.
+1. Oversampled k candidates are rescored using either the uncompressed original vectors for scalar quantization, or the dot product of binary quantization.
 1. After rescoring, results are adjusted so that more relevant matches appear first.
 
+Oversampling for scalar quantized vectors requires the availability of the original full precision vectors. Oversampling for binary quantized vectors can use either full precision vectors (`preserveOriginals`) or the dot product of the binary vector (`discardOriginals`). If you're optimizing vector storage, make sure to keep the full precision vectors in the index if you need them for rescoring purposes. For more information, see [Eliminate optional vector instances from storage](vector-search-how-to-storage-options.md).
+
 ## Add "compressions" to a search index
 
 This section explains how to specify a `vectorsSearch.compressions` section in the index. The following example shows a partial index definition with a fields collection that includes a vector field.

@@ -9,7 +9,7 @@ ms.update-cycle: 180-days
 ms.custom:
   - build-2024
 ms.topic: how-to
-ms.date: 06/19/2025
+ms.date: 09/29/2025
 ---
 
 # Create a vector query in Azure AI Search
@@ -93,9 +93,9 @@ This section shows you the basic structure of a vector query. You can use the Az
 
 If you're migrating from [**2023-07-01-Preview**](/rest/api/searchservice/index-preview), there are breaking changes. For more information, see [Upgrade to the latest REST API](search-api-migration.md).
 
-### [**2024-07-01**](#tab/query-2024-07-01)
+### [**2025-09-01**](#tab/query-2025-09-01)
 
-[**2024-07-01**](/rest/api/searchservice/search-service-api-versions#2024-07-01) is the stable REST API version of [Search POST](/rest/api/searchservice/documents/search-post). This version supports:
+The stable version supports:
 
 + `vectorQueries` is the construct for vector search.
 + `vectorQueries.kind` set to `vector` for a vector array or `text` if the input is a string and if you [have a vectorizer](#query-with-integrated-vectorization).
@@ -108,7 +108,7 @@ If you're migrating from [**2023-07-01-Preview**](/rest/api/searchservice/index-
 In the following example, the vector is a representation of this string: `"what Azure services support full text search"`. The query targets the `contentVector` field and returns `k` results. The actual vector has 1,536 embeddings, which are trimmed in this example for readability.
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-07-01
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -133,9 +133,9 @@ api-key: {{admin-api-key}}
 }
 ```
 
-### [**2024-05-01-preview**](#tab/query-2024-05-01-preview)
+### [**2025-08-01-preview**](#tab/query-2025-08-01-preview)
 
-[**2024-05-01-preview**](/rest/api/searchservice/search-service-api-versions#2024-05-01-preview) is the latest preview API version of [Search - POST](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2024-05-01-preview&tabs=HTTP&preserve-view=true). It supports the same vector query syntax as **2024-07-01**, but it has extra parameters for hybrid search and minimum thresholds for excluding weaker results.
+[**2025-08-01-preview**](/rest/api/searchservice/search-service-api-versions#2025-08-01-preview) is the latest preview API version of [Search - POST](/rest/api/searchservice/documents/search-post?view=rest-searchservice-2025-08-01-preview&tabs=HTTP&preserve-view=true). It supports the same vector query syntax as **2025-09-01**, but it has extra parameters for hybrid search and minimum thresholds for excluding weaker results.
 
 This preview adds:
 
@@ -145,7 +145,7 @@ This preview adds:
 In the following example, the vector is a representation of this string: `"what Azure services support full text search"`. The query targets the `contentVector` field and returns `k` results. The actual vector has 1,536 embeddings, which are trimmed in this example for readability.
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-05-01-preview
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-08-01-preview
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -267,7 +267,7 @@ You can set the `vectorQueries.fields` property to multiple vector fields. The v
 When querying multiple vector fields, ensure that each one contains embeddings from the same embedding model. The query should also be generated from the same embedding model.
 
 ```http
-POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2024-07-01
+POST https://{{search-service-name}}.search.windows.net/indexes/{{index-name}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -338,7 +338,7 @@ Search indexes can't store images. Assuming that your index includes a field for
 
 ## Query with integrated vectorization
 
-This section shows a vector query that invokes the [integrated vectorization](vector-search-integrated-vectorization.md) to convert a text or [image query](search-get-started-portal-image-search.md) into a vector. We recommend the stable [**2024-07-01**](/rest/api/searchservice/documents/search-post) REST API, Search Explorer, or newer Azure SDK packages for this feature.
+This section shows a vector query that invokes the [integrated vectorization](vector-search-integrated-vectorization.md) to convert a text or [image query](search-get-started-portal-image-search.md) into a vector. We recommend the stable [**2025-09-01**](/rest/api/searchservice/documents/search-post) REST API, Search Explorer, or newer Azure SDK packages for this feature.
 
 A prerequisite is a search index that has a [vectorizer configured and assigned](vector-search-how-to-configure-vectorizer.md) to a vector field. The vectorizer provides connection information to an embedding model used at query time.
 
@@ -358,7 +358,7 @@ Search Explorer supports integrated vectorization at query time. If your index c
 
    Alternatively, you can select **View** > **JSON view** to view or modify the query. If vectors are present, Search Explorer sets up a vector query automatically. You can use the JSON view to select fields for use in the searche and response, add filters, and construct more advanced queries, such as [hybrid queries](hybrid-search-how-to-query.md). To see a JSON example, select the REST API tab in this section.
 
-### [**REST API**](#tab/builtin-2024-07-01)
+### [**REST API**](#tab/builtin-2025-09-01)
 
 1. Use [Index - GET](/rest/api/searchservice/indexes/get) to return the index definition and check for the presence of a vectorizer configuration. Look for `vectorizers` in your index definition. It should specify a deployed embedding model.
 
@@ -372,7 +372,7 @@ Search Explorer supports integrated vectorization at query time. If your index c
 Here's a simple example of a query that's vectorized at query time. The text string is vectorized and then used to query the `descriptionVector` field.
 
 ```http
-POST https://{{search-service}}.search.windows.net/indexes/{{index}}/docs/search?api-version=2024-07-01
+POST https://{{search-service}}.search.windows.net/indexes/{{index}}/docs/search?api-version=2025-09-01
 {
     "select": "title, genre, description",
     "vectorQueries": [
@@ -391,7 +391,7 @@ Here's a [hybrid query](hybrid-search-how-to-query.md) that uses integrated vect
 In this example, the search engine makes three vectorization calls to the vectorizers assigned to `descriptionVector`, `synopsisVector`, and `authorBioVector` in the index. The resulting vectors are used to retrieve documents against their respective fields. The search engine also executes a keyword search on the `search` query, which is `"mystery novel set in London"`.
 
 ```http
-POST https://{{search-service}}.search.windows.net/indexes/{{index}}/docs/search?api-version=2024-07-01
+POST https://{{search-service}}.search.windows.net/indexes/{{index}}/docs/search?api-version=2025-09-01
 Content-Type: application/json
 api-key: {{admin-api-key}}
 {
@@ -473,7 +473,7 @@ Weights are used when calculating the [RRF scores](hybrid-search-ranking.md#weig
 The following example is a hybrid query with two vector query strings and one text string. Weights are assigned to the vector queries. The first query is 0.5 or half the weight, reducing its importance in the request. The second vector query is twice as important.
 
 ```http
-POST https://[service-name].search.windows.net/indexes/[index-name]/docs/search?api-version=2024-07-01
+POST https://[service-name].search.windows.net/indexes/[index-name]/docs/search?api-version=2025-09-01
 
     { 
       "vectorQueries": [ 

@@ -9,12 +9,17 @@ ms.update-cycle: 180-days
 ms.custom:
   - ignite-2024
 ms.topic: how-to
-ms.date: 09/19/2025
+ms.date: 09/29/2025
 ---
 
 # Eliminate optional vector instances from storage
 
-Azure AI Search stores multiple copies of vector fields that are used in specific workloads. If you don't need to support a specific behavior, like returning raw vectors in a query response, you can set properties in the index that omit storage for that workload.
+Azure AI Search stores multiple copies of vector fields that are used in specific workloads. If your search scenarios don't require all of these copies, you can omit storage for that workload. 
+
+Use cases where an extra copy is used include:
+
+- Returning raw vectors in a query response or supporting incremental updates to vector content.
+- Rescoring compressed (quantized) vectors as a query optimization technique.
 
 Removing storage is irreversible and requires reindexing if you want it back.
 
@@ -24,33 +29,21 @@ Removing storage is irreversible and requires reindexing if you want it back.
 
 ## How vector fields are stored
 
-For every vector field, there are up to three copies of the vectors, each serving a different purpose:
-
-| Instance | Usage | Controlled using |
-|----------|-------|------------------|
-| Source vectors received during document indexing (JSON data) | Used for incremental data refresh with `merge` or `mergeOrUpload` indexing action. Also used to return "retrievable" vectors in the query response. | `stored` property on vector fields |
-| Original full-precision vectors (binary data) | Used for internal index operations and for exhaustive KNN search in older API versions. For compressed vectors, it's also used for `preserveOriginals` rescoring on an oversampled candidate set of results from ANN search. This applies to vector fields that undergo [scalar or binary quantization](vector-search-how-to-quantization.md). | `rescoringOptions.rescoreStorageMethod` property in `vectorSearch.compressions`. |
-| Vectors in the [HNSW graph for Approximate Nearest Neighbors (ANN) search](vector-search-overview.md) (HNSW graph) or vectors for exhaustive K-Nearest Neighbors (eKNN index) | Used for query execution. Consists of either full-precision vectors (when no compression is applied) or quantized vectors. | Essential. There are no parameters for removing this instance. |
-
-You can set properties that permanently discard the first two instances (JSON data and binary data) from vector storage, but not the last instance.
-
-To offset lossy compression for HNSW, you can keep the second instance (binary data) for rescoring purposes to improve ANN search quality. For eKNN, only scalar quantization is supported, and rescoring isn't an option. In newer API versions like the latest preview, the second instance isn't kept for eKNN because the third instance provides full-precision vectors in an eKNN index.
-
-### Indexes created with 2024-11-01-preview or later API versions
+| Instance | Usage | Required for search | How removed |
+|----------|-------|---------------------|-------------|
+| Vectors in the [HNSW graph for Approximate Nearest Neighbors (ANN) search](vector-search-overview.md) (HNSW graph) or vectors for exhaustive K-Nearest Neighbors (eKNN index) | Used for query execution. Consists of either full-precision vectors (when no compression is applied) or quantized vectors. | Essential | There are no parameters for removing this instance. |
+| Source vectors received during document indexing (JSON data) | Used for incremental data refresh with `merge` or `mergeOrUpload` indexing actions. Also used to return "retrievable" vectors in the query response. | No | Set `stored` property to false. |
+| Original full-precision vectors (binary data) <sup>1</sup> | For compressed vectors, it's used for `preserveOriginals` rescoring on an oversampled candidate set of results from ANN search. This applies to vector fields that undergo [scalar or binary quantization](vector-search-how-to-quantization.md), and it applies to queries using the HNSW graph. If you're using eKNN, all vectors are in scope for the query, so rescoring has no effect and thus not supported. | No | Set `rescoringOptions.rescoreStorageMethod` property to `discardOriginals` in `vectorSearch.compressions`. |
 
-For indexes created with the 2024-11-01-preview or a later API with uncompressed vector fields, the second and third instances (binary data and HNSW graph) are combined as part of our cost reduction investments, reducing overall storage. A newer generation index with consolidated vectors is functionally equivalent to older indexes, but uses less storage. Physical data structures are established on a Create Index request, so you must delete and recreate the index to realize the storage reductions.
-
-If you choose [vector compression](vector-search-how-to-configure-compression-storage.md), AI Search compresses (quantizes) the in-memory portion of the vector index. Since memory is often a primary constraint for vector indexes, this practice allows you to store more vectors within the same search service. However, lossy compression equates to less information in the index, which can affect search quality.
-
-To mitigate the loss in information, you can [enable "rescoring" and "oversampling" options](vector-search-how-to-quantization.md#supported-rescoring-techniques) to help maintain quality. The effect is retrieval of a larger set of candidate documents from the compressed index, with recomputation of similarity scores using the original vectors or the dot product. For rescoring to work, original vectors must be retained in storage for certain scenarios. As a result, while quantization reduces memory usage (vector index size usage), it slightly increases storage requirements since both compressed and original vectors are stored. The extra storage is approximately equal to the size of the compressed index.
+<sup>1</sup> This copy is also for internal index operations and for exhaustive KNN search in older API versions, on indexes created using the 2023 APIs. On newer indexes, an eKNN-configured field consists of full-precision vectors so no extra copy is needed.
 
 ## Remove source vectors (JSON data)
 
 In a vector field definition, `stored` is a boolean property that determines whether storage is allocated for retrievable vector content obtained during indexing (the source instance). By default, `stored` is set to `true`. If you don't need raw vector content in a query response, changing `stored` to `false` can save up to 50% storage per field.
 
 Considerations for setting `"stored": false`:
 
-- Because vectors aren't human readable, you can omit them from results sent to LLMs in RAG scenarios or from results rendered on a search page. However, keep them if you're using vectors in a downstream process that consumes vector content.
+- Because vectors aren't human readable, you can generally omit them from results sent to LLMs in RAG scenarios or from results rendered on a search page. However, you should keep them if you're using vectors in a downstream process that consumes vector content.
 
 - If your indexing strategy uses [partial document updates](search-howto-reindex.md#update-content), such as `merge` or `mergeOrUpload` on an existing document, setting `"stored": false` prevents content updates to those fields during the merge. You must include the entire vector field (and nonvector fields you're updating) in each reindexing operation. Otherwise, the vector data is lost without an error or warning. To avoid this risk altogether, set `"stored": true`.
 
@@ -60,7 +53,7 @@ Considerations for setting `"stored": false`:
 For new vector fields in a search index, set `"stored": false` to permanently remove retrievable storage for the vector field. The following example shows a vector field definition with the `stored` property.
 
 ```http
-PUT https://[service-name].search.windows.net/indexes/demo-index?api-version=2024-07-01 
+PUT https://[service-name].search.windows.net/indexes/demo-index?api-version=2025-09-01@search.rerankerBoostedScore 
   Content-Type: application/json  
   api-key: [admin key]  
 
@@ -89,44 +82,37 @@ PUT https://[service-name].search.windows.net/indexes/demo-index?api-version=202
 
 - Defaults are `"stored": true` and `"retrievable": false`. In a default configuration, a retrievable copy is stored but isn't automatically returned in results. When `stored` is `true`, you can toggle `retrievable` between `true` and `false` at any time without having to rebuild an index. When `stored` is `false`, `retrievable` must be `false` and can't be changed.
 
-## Remove full-precision vectors (binary data)
+## Remove full-precision vectors
 
-[!INCLUDE [Feature preview](./includes/previews/preview-generic.md)]
+Original full-precision vectors are used in rescoring operations over compressed (quantized) vectors. The intent of rescoring is to mitigate the loss in information due to compression. The effect of rescoring is retrieval of a larger set of candidate documents from the compressed index, with recomputation of similarity scores using the original vectors or the dot product. For rescoring to work, original vectors must be retained in storage for certain scenarios. As a result, while quantization reduces memory usage (vector index size usage), it slightly increases storage requirements since both compressed and original vectors are stored. The extra storage is approximately equal to the size of the compressed index.
 
-When you compress vectors using either scalar or binary quantization, query execution is over the quantized vectors. In this case, you only need the original full-precision vectors (binary data) if you want to rescore.
+Rescoring requirements by quantization approach:
 
-If you use newer preview APIs *and* binary quantization, you can safely discard full-precision vectors because rescoring strategies now use the dot product of a binary embedding, which produces high quality search results, without having to reference full-precision vectors in the index.
+- Rescoring of scalar quantized vectors requires retention of the original full-precision vectors.
 
-The `rescoreStorageMethod` property controls whether full-precision vectors are stored. The guidance for whether to retain full-precision vectors is:
+- Rescoring of binary quantized vectors can use either the original full-precision vectors, or the dot product of the binary embedding, which produces high quality search results, without having to reference full-precision vectors in the index.
 
-- For scalar quantization, preserve original full-precision vectors in the index because they're required for rescore.
-- For binary quantization, preserve original full-precision vectors for the highest quality of rescoring, or discard full-precision vectors (requires 2025-03-01-preview) if you want to rescore based on the dot product of the binary embeddings.
+Rescoring recommendations:
 
-Vector storage strategies have been evolving over the last several releases. Index creation date and API version determine your storage options.
-
-| API version | Applies to | Remove full-precision vectors |
-|--|--|--|
-| 2024-07-01 and earlier | Not applicable. | There's no mechanism for removing full-precision vectors. |
-| 2024-11-01-preview | Binary embeddings | Use `rescoreStorageMethod.discardOriginals` to remove full-precision vectors, but doing so prevents rescoring. `enableRescoring` must be false if originals are gone.|
-| 2025-03-01-preview | Binary embeddings | Use `rescoreStorageMethod.discardOriginals` to remove full-precision vectors in the index while still retaining rescore options. In this preview, rescoring is possible because the technique changed. The dot product of the binary embeddings is used on the rescore, producing high quality search results equivalent to or better than earlier techniques based on full-precision vectors. |
+- For scalar quantization, preserve original full-precision vectors in the index because they're required for rescore.
 
-Notice that scalar isn't listed in the table. If you use scalar quantization, you must retain original full-precision vectors if you want to rescore.
+- For binary quantization, either preserve original full-precision vectors for the highest quality of rescoring, or discard full-precision vectors if you want to rescore based on the dot product of the binary embeddings.
 
-In `vectorSearch.compressions`, the `rescoreStorageMethod` property is set to `preserveOriginals` by default, which retains full-precision vectors for [oversampling and rescoring capabilities](vector-search-how-to-quantization.md#add-compressions-to-a-search-index) to reduce the effect of lossy compression on the HNSW graph. If you don't need full-precision vectors, you can reduce vector storage by setting `rescoreStorageMethod` to `discardOriginals`.
+The `rescoreStorageMethod` property controls whether full-precision vectors are stored. In `vectorSearch.compressions`, the `rescoreStorageMethod` property is set to `preserveOriginals` by default, which retains full-precision vectors for [oversampling and rescoring capabilities](vector-search-how-to-quantization.md#add-compressions-to-a-search-index) to reduce the effect of lossy compression on the HNSW graph. If you don't need rescoring, of if you used binary quantization and the dot product for rescoring, you can reduce vector storage by setting `rescoreStorageMethod` to `discardOriginals`.
 
 > [!IMPORTANT]
 > Setting the `rescoreStorageMethod` property is irreversible and can adversely affect search quality, although the degree depends on the compression method and any mitigations you apply.
 
 To set this property:
 
-1. Use [Create Index (preview)](/rest/api/searchservice/indexes/create?view=rest-searchservice-2025-03-01-preview&preserve-view=true) or [Create or Update Index (preview)](/rest/api/searchservice/indexes/create-or-update?view=rest-searchservice-2025-03-01-preview&preserve-view=true) REST APIs, or an Azure SDK beta package providing the feature.
+1. Use [Create Index](/rest/api/searchservice/indexes/create) or [Create or Update Index](/rest/api/searchservice/indexes/create-or-update) REST APIs, or an Azure SDK.
 
 1. Add a `vectorSearch` section to your index with profiles, algorithms, and compressions.
 
 1. Under `vectorSearch.compressions`, add `rescoringOptions` with `enableRescoring` set to true, `defaultOversampling` set to a positive integer, and `rescoreStorageMethod` set to `discardOriginals` for binary quantization and `preserveOriginals` for scalar quantization.
 
     ```http
-    PUT https://[service-name].search.windows.net/indexes/demo-index?api-version=2025-03-01-preview
+    PUT https://[service-name].search.windows.net/indexes/demo-index?api-version=2025-09-01
     
     {
         "name": "demo-index",
@@ -186,3 +172,5 @@ To set this property:
         }
     }
     ```
+> [!NOTE]
+> Vector storage strategies have been evolving over the last several releases. Index creation date and API version determine your storage options. For example, in the 2024-11-01-preview, if you set `discardOriginals` to remove full-precision vectors, there was no rescoring for binary quantization because the dot product approach wasn't available. We recommend using the latest APIs for the best mitigation options.

@@ -92,7 +92,7 @@ Usage and quota are reported in bytes.
 Here's GET Service Statistics:
 
 ```http
-GET {{baseUrl}}/servicestats?api-version=2024-07-01  HTTP/1.1
+GET {{baseUrl}}/servicestats?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     api-key: {{apiKey}}
 ```
@@ -134,7 +134,7 @@ Response includes metrics for `storageSize`, which doesn't distinguish between v
 You can also send a GET Index Statistics to get the physical size of the index on disk, plus the in-memory size of the vector fields.
 
 ```http
-GET {{baseUrl}}/indexes/vector-healthplan-idx/stats?api-version=2024-07-01  HTTP/1.1
+GET {{baseUrl}}/indexes/vector-healthplan-idx/stats?api-version=2025-09-01  HTTP/1.1
     Content-Type: application/json
     api-key: {{apiKey}}
 ```