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Update Search with x-ms-client-names and a few new requires (#26355)
* Update Search with x-ms-client-names and a few new requires * Make VectorizableTextQuery.text required * Renamce SemanticSetting.defaultConfiguration to defaultConfigurationName to clarify it's a name of a configuration * SemanticConfiguration.semanticPriorizedFields -> prioritizedFields as semantic is redundant * Remove VectorQuery changes as they aren't final * Remove SearchRequest.vectorQueries rename, fixed typo in SemanticSearch * Add custom word
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‎custom-words.txt‎

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@@ -3738,6 +3738,7 @@ usedCPUMHz
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totalCPUMHz
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docon
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DialOut
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Vectorizable
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vectorizers
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Entra
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‎specification/search/data-plane/Azure.Search/preview/2023-10-01-Preview/searchindex.json‎

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@@ -266,7 +266,7 @@
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"fail"
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],
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"x-ms-enum": {
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"name": "SemanticErrorHandling",
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"name": "SemanticErrorMode",
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"modelAsString": true,
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"values": [
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{
@@ -405,7 +405,7 @@
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"extractive"
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],
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"x-ms-enum": {
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"name": "Answers",
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"name": "QueryAnswerType",
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"modelAsString": true,
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"values": [
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{
@@ -535,7 +535,7 @@
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"extractive"
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],
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"x-ms-enum": {
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"name": "Captions",
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"name": "QueryCaptionType",
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"modelAsString": true,
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"values": [
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{
@@ -1214,6 +1214,7 @@
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"description": "A single bucket of a facet query result. Reports the number of documents with a field value falling within a particular range or having a particular value or interval."
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},
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"AnswerResult": {
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"x-ms-client-name": "QueryAnswerResult",
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"properties": {
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"score": {
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"type": "number",
@@ -1242,6 +1243,7 @@
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"description": "An answer is a text passage extracted from the contents of the most relevant documents that matched the query. Answers are extracted from the top search results. Answer candidates are scored and the top answers are selected."
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},
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"CaptionResult": {
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"x-ms-client-name": "QueryCaptionResult",
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"properties": {
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"text": {
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"type": "string",
@@ -1266,7 +1268,7 @@
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"transient"
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],
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"x-ms-enum": {
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"name": "SemanticPartialResponseReason",
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"name": "SemanticErrorReason",
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"modelAsString": true,
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"values": [
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{
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"rerankedResults"
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],
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"x-ms-enum": {
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"name": "SemanticPartialResponseType",
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"name": "SemanticSearchResultsType",
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"modelAsString": true,
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"values": [
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{
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"partial"
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],
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"x-ms-enum": {
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"name": "QueryResultDocumentSemanticFieldState",
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"name": "SemanticFieldState",
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"modelAsString": true,
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"values": [
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{
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"fail"
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],
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"x-ms-enum": {
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"name": "SemanticErrorHandling",
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"name": "SemanticErrorMode",
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"modelAsString": true,
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"values": [
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{
@@ -1891,6 +1893,9 @@
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"description": "The vector representation of a search query."
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}
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},
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"required": [
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"vector"
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],
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"description": "The query parameters to use for vector search when a raw vector value is provided."
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},
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"VectorizableTextQuery": {
@@ -1907,6 +1912,9 @@
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"description": "The text to be vectorized to perform a vector search query."
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}
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},
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"required": [
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"text"
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],
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"description": "The query parameters to use for vector search when a text value that needs to be vectorized is provided."
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},
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"VectorQueryKind": {

‎specification/search/data-plane/Azure.Search/preview/2023-10-01-Preview/searchservice.json‎

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@@ -6049,8 +6049,10 @@
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"description": "Ranking function based on the Okapi BM25 similarity algorithm. BM25 is a TF-IDF-like algorithm that includes length normalization (controlled by the 'b' parameter) as well as term frequency saturation (controlled by the 'k1' parameter)."
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},
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"SemanticSettings": {
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"x-ms-client-name": "SemanticSearch",
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"properties": {
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"defaultConfiguration": {
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"x-ms-client-name": "defaultConfigurationName",
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"type": "string",
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"description": "Allows you to set the name of a default semantic configuration in your index, making it optional to pass it on as a query parameter every time."
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},
@@ -6093,19 +6095,22 @@
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"description": "Defines a specific configuration to be used in the context of semantic capabilities."
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},
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"PrioritizedFields": {
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"x-ms-client-name": "SemanticPrioritizedFields",
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"properties": {
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"titleField": {
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"$ref": "#/definitions/SemanticField",
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"description": "Defines the title field to be used for semantic ranking, captions, highlights, and answers. If you don't have a title field in your index, leave this blank."
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},
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"prioritizedContentFields": {
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"x-ms-client-name": "contentFields",
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"type": "array",
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"items": {
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"$ref": "#/definitions/SemanticField"
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},
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"description": "Defines the content fields to be used for semantic ranking, captions, highlights, and answers. For the best result, the selected fields should contain text in natural language form. The order of the fields in the array represents their priority. Fields with lower priority may get truncated if the content is long."
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},
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"prioritizedKeywordsFields": {
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"x-ms-client-name": "keywordsFields",
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"type": "array",
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"items": {
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"$ref": "#/definitions/SemanticField"
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"x-nullable": false
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}
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},
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"required": [
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"fieldName"
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],
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"description": "A field that is used as part of the semantic configuration."
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},
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"VectorSearch": {
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"x-nullable": false
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},
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"algorithm": {
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"x-ms-client-name": "algorithmConfigurationName",
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"type": "string",
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"description": "The name of the vector search algorithm configuration that specifies the algorithm and optional parameters.",
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"x-nullable": false
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"description": "Contains configuration options specific to the algorithm used during indexing or querying."
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},
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"HnswVectorSearchAlgorithmConfiguration": {
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"x-ms-client-name": "HnswAlgorithmConfiguration",
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"type": "object",
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"x-ms-discriminator-value": "hnsw",
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"allOf": [
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"description": "Contains the parameters specific to the HNSW algorithm."
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},
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"ExhaustiveKnnVectorSearchAlgorithmConfiguration": {
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"x-ms-client-name": "ExhaustiveKnnAlgorithmConfiguration",
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"type": "object",
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"x-ms-discriminator-value": "exhaustiveKnn",
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"allOf": [
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"x-nullable": true
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},
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"dimensions": {
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"x-ms-client-name": "vectorSearchDimensions",
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"type": "integer",
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"format": "int32",
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"x-nullable": true,
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"description": "The dimensionality of the vector field."
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},
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"vectorSearchProfile": {
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"x-ms-client-name": "vectorSearchProfileName",
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"type": "string",
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"x-nullable": true,
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"description": "The name of the vector search profile that specifies the algorithm and vectorizer to use when searching the vector field."
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"externalDocs": {
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"url": "https://docs.microsoft.com/azure/search/semantic-search-overview"
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},
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"x-ms-client-name": "SemanticSettings",
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"x-ms-client-name": "SemanticSearch",
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"x-nullable": true
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},
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"vectorSearch": {
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"description": "A parameter that provides various ways to mask the personal information detected in the input text. Default is 'none'."
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},
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"maskingCharacter": {
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"x-ms-client-name": "mask",
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"type": "string",
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"x-nullable": true,
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"maxLength": 1,
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"authResourceId": {
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"type": "string",
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"x-nullable": true,
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"x-ms-format": "arm-id",
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"description": "Applies to custom skills that connect to external code in an Azure function or some other application that provides the transformations. This value should be the application ID created for the function or app when it was registered with Azure Active Directory. When specified, the custom skill connects to the function or app using a managed ID (either system or user-assigned) of the search service and the access token of the function or app, using this value as the resource id for creating the scope of the access token."
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},
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"authIdentity": {

‎specification/search/data-plane/Azure.Search/stable/2023-11-01/searchindex.json‎

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@@ -379,7 +379,7 @@
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"fail"
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],
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"x-ms-enum": {
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"name": "SemanticErrorHandling",
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"name": "SemanticErrorMode",
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"modelAsString": true,
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"values": [
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{
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"extractive"
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],
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"x-ms-enum": {
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"name": "Answers",
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"name": "QueryAnswerType",
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"modelAsString": true,
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"values": [
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{
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"extractive"
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],
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"x-ms-enum": {
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"name": "Captions",
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"name": "QueryCaptionType",
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"modelAsString": true,
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"values": [
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{
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"description": "The vector representation of a search query."
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}
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},
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"required": [
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"vector"
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],
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"description": "The query parameters to use for vector search when a raw vector value is provided."
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},
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"VectorQueryKind": {
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"description": "Describes an error condition for the API."
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},
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"AnswerResult": {
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"x-ms-client-name": "QueryAnswerResult",
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"properties": {
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"score": {
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"type": "number",
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"description": "An answer is a text passage extracted from the contents of the most relevant documents that matched the query. Answers are extracted from the top search results. Answer candidates are scored and the top answers are selected."
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},
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"CaptionResult": {
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"x-ms-client-name": "QueryCaptionResult",
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"properties": {
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"text": {
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"type": "string",
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"transient"
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],
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"x-ms-enum": {
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"name": "SemanticPartialResponseReason",
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"name": "SemanticErrorReason",
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"modelAsString": true,
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"values": [
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{
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"rerankedResults"
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],
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"x-ms-enum": {
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"name": "SemanticPartialResponseType",
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"name": "SemanticSearchResultsType",
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"modelAsString": true,
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"values": [
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{
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"fail"
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],
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"x-ms-enum": {
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"name": "SemanticErrorHandling",
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"name": "SemanticErrorMode",
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"modelAsString": true,
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"values": [
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{

‎specification/search/data-plane/Azure.Search/stable/2023-11-01/searchservice.json‎

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"x-nullable": false
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},
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"algorithm": {
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"x-ms-client-name": "algorithmConfigurationName",
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"type": "string",
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"description": "The name of the vector search algorithm configuration that specifies the algorithm and optional parameters.",
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"x-nullable": false
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"description": "Contains configuration options specific to the algorithm used during indexing or querying."
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},
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"HnswVectorSearchAlgorithmConfiguration": {
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"x-ms-client-name": "HnswAlgorithmConfiguration",
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"type": "object",
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"x-ms-discriminator-value": "hnsw",
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"allOf": [
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"description": "Contains the parameters specific to the HNSW algorithm."
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},
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"ExhaustiveKnnVectorSearchAlgorithmConfiguration": {
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"x-ms-client-name": "ExhaustiveKnnAlgorithmConfiguration",
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"type": "object",
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"x-ms-discriminator-value": "exhaustiveKnn",
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"allOf": [
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"x-nullable": true
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},
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"dimensions": {
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"x-ms-client-name": "vectorSearchDimensions",
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"type": "integer",
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"format": "int32",
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"x-nullable": true,
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"description": "The dimensionality of the vector field."
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},
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"vectorSearchProfile": {
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"x-ms-client-name": "vectorSearchProfileName",
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"type": "string",
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"x-nullable": true,
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"description": "The name of the vector search profile that specifies the algorithm to use when searching the vector field."
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"externalDocs": {
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"url": "https://learn.microsoft.com/azure/search/semantic-search-overview"
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},
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"x-ms-client-name": "SemanticSettings",
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"x-ms-client-name": "SemanticSearch",
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"x-nullable": true
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},
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"vectorSearch": {
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"description": "A parameter that provides various ways to mask the personal information detected in the input text. Default is 'none'."
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},
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"maskingCharacter": {
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"x-ms-client-name": "mask",
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"type": "string",
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"x-nullable": true,
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"maxLength": 1,
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"description": "Describes an error condition for the API."
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},
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"SemanticSettings": {
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"x-ms-client-name": "SemanticSearch",
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"properties": {
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"defaultConfiguration": {
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"x-ms-client-name": "defaultConfigurationName",
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"type": "string",
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"description": "Allows you to set the name of a default semantic configuration in your index, making it optional to pass it on as a query parameter every time."
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},
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"description": "Defines a specific configuration to be used in the context of semantic capabilities."
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},
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"PrioritizedFields": {
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"x-ms-client-name": "SemanticPrioritizedFields",
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"properties": {
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"titleField": {
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"$ref": "#/definitions/SemanticField",
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"description": "Defines the title field to be used for semantic ranking, captions, highlights, and answers. If you don't have a title field in your index, leave this blank."
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},
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"prioritizedContentFields": {
10820+
"x-ms-client-name": "contentFields",
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"type": "array",
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"items": {
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"$ref": "#/definitions/SemanticField"
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},
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"description": "Defines the content fields to be used for semantic ranking, captions, highlights, and answers. For the best result, the selected fields should contain text in natural language form. The order of the fields in the array represents their priority. Fields with lower priority may get truncated if the content is long."
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},
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"prioritizedKeywordsFields": {
10828+
"x-ms-client-name": "keywordsFields",
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"type": "array",
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"items": {
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"$ref": "#/definitions/SemanticField"
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"x-nullable": false
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}
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},
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"required": [
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"fieldName"
10851+
],
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"description": "A field that is used as part of the semantic configuration."
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}
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},

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