Package com.azure.search.documents.models
package com.azure.search.documents.models
Package containing the data models for SearchIndexClient.
Client that can be used to query an index and upload, merge, or delete documents.
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ClassDescriptionThe result of Autocomplete requests.Specifies the mode for Autocomplete.Parameter group.The result of Autocomplete query.Contains debugging information that can be used to further explore your search results.Contains debugging information that can be used to further explore your search results.A single bucket of a facet query result.Determines whether the count and facets should includes all documents that matched the search query, or only the documents that are retrieved within the 'maxTextRecallSize' window.TThe query parameters to configure hybrid search behaviors.IndexAction<T>Represents an index action that operates on a document.The operation to perform on a document in an indexing batch.Contains a batch of document write actions to send to the index.An
IndexBatchExceptionis thrown whenever Azure AI Search index call was only partially successful.Options for document index operations.Response containing the status of operations for all documents in the indexing request.Status of an indexing operation for a single document.Configuration for how semantic search returns answers to the search.An answer is a text passage extracted from the contents of the most relevant documents that matched the query.This parameter is only valid if the query type is `semantic`.Configuration for how semantic search captions search results.Captions are the most representative passages from the document relatively to the search query.This parameter is only valid if the query type is `semantic`.Enables a debugging tool that can be used to further explore your search results.The language of the query.Detailed scoring information for an individual element of a complex collection.The raw concatenated strings that were sent to the semantic enrichment process.Description of fields that were sent to the semantic enrichment process, as well as how they were used.The breakdown of subscores between the text and vector query components of the search query for this document.Configuration for how semantic search rewrites a query.Contains debugging information specific to query rewrites.This parameter is only valid if the query type is `semantic`.Contains debugging information specific to query rewrites.Improve search recall by spell-correcting individual search query terms.Specifies the syntax of the search query.A single bucket of a range facet query result that reports the number of documents with a field value falling within a particular range.Represents a parameter value to be used in scoring functions (for example, referencePointParameter).A value that specifies whether we want to calculate scoring statistics (such as document frequency) globally for more consistent scoring, or locally, for lower latency.Cloud audiences available for Search.Specifies whether any or all of the search terms must be matched in order to count the document as a match.Additional parameters for searchGet operation.Contains a document found by a search query, plus associated metadata.The results of the vector query will filter based on the '@search.score' value.The SemanticDebugInfo model.Allows the user to choose whether a semantic call should fail completely, or to return partial results.Reason that a partial response was returned for a semantic ranking request.The way the field was used for the semantic enrichment process.Type of query rewrite that was used for this request.Parameters for performing vector searches.The document-level results for asemanticsearch.The page-level results for asemanticsearch.Type of partial response that was returned for a semantic ranking request.A single vector field result.Parameter group.A result containing a document found by a suggestion query, plus associated metadata.The BM25 or Classic score for the text portion of the query.A single bucket of a simple or interval facet query result that reports the number of documents with a field falling within a particular interval or having a specific value.Determines whether or not filters are applied before or after the vector search is performed.The query parameters to use for vector search when a base 64 encoded binary of an image that needs to be vectorized is provided.The query parameters to use for vector search when an url that represents an image value that needs to be vectorized is provided.The query parameters to use for vector search when a text value that needs to be vectorized is provided.The query parameters to use for vector search when a raw vector value is provided.The query parameters for vector and hybrid search queries.The kind of vector query being performed.The VectorsDebugInfo model.Parameters for performing vector searches.The results of the vector query will be filtered based on the vector similarity metric.The threshold used for vector queries.The kind of vector query being performed.