com.azure.search.documents.indexes.models

The name of the embedding model from the Azure AI Foundry Catalog that will be called.

The multi-region account of an Azure AI service resource that's attached to a skillset.

The account key of an Azure AI service resource that's attached to a skillset, to be used with the resource's subdomain.

The result of testing an analyzer on text.

Specifies some text and analysis components used to break that text into tokens.

Information about a token returned by an analyzer.

Converts alphabetic, numeric, and symbolic Unicode characters which are not in the first 127 ASCII characters (the "Basic Latin" Unicode block) into their ASCII equivalents, if such equivalents exist.

Credentials of a registered application created for your search service, used for authenticated access to the encryption keys stored in Azure Key Vault.

Configuration for Azure Blob Storage knowledge source.

Parameters for Azure Blob Storage knowledge source.

Specifies the properties for connecting to an AML vectorizer.

Specifies an Azure Machine Learning endpoint deployed via the Azure AI Foundry Model Catalog for generating the vector embedding of a query string.

Allows you to generate a vector embedding for a given text input using the Azure OpenAI resource.

The Azure Open AI model name that will be called.

Specifies the Azure OpenAI resource used to vectorize a query string.

Specifies the parameters for connecting to the Azure OpenAI resource.

Ranking function based on the Okapi BM25 similarity algorithm.

Contains configuration options specific to the binary quantization compression method used during indexing and querying.

Specifies the data to extract from Azure blob storage and tells the indexer which data to extract from image content when "imageAction" is set to a value other than "none".

Determines how to process embedded images and image files in Azure blob storage.

Determines algorithm for text extraction from PDF files in Azure blob storage.

Represents the parsing mode for indexing from an Azure blob data source.

Base type for character filters.

Defines the names of all character filters supported by the search engine.

Common language model parameters for Chat Completions.

Specifies how 'extraParameters' should be handled by Azure AI Foundry.

Determines how the language model's response should be serialized.

Specifies how the LLM should format the response.

Object defining the custom schema the model will use to structure its output.

Properties for JSON schema response format.

A skill that calls a language model via Azure AI Foundry's Chat Completions endpoint.

Forms bigrams of CJK terms that are generated from the standard tokenizer.

Legacy similarity algorithm which uses the Lucene TFIDFSimilarity implementation of TF-IDF.

Grammar-based tokenizer that is suitable for processing most European-language documents.

Base type for describing any Azure AI service resource attached to a skillset.

The multi-region account key of an Azure AI service resource that's attached to a skillset.

Construct bigrams for frequently occurring terms while indexing.

A skill that enables scenarios that require a Boolean operation to determine the data to assign to an output.

A skill that leverages Azure AI Content Understanding to process and extract structured insights from documents, enabling enriched, searchable content for enhanced document indexing and retrieval.

Controls the cardinality for chunking the content.

Controls the cardinality of the chunk unit.

Controls the cardinality of the content extracted from the document by the skill.

Defines options to control Cross-Origin Resource Sharing (CORS) for an index.

Resources created by the knowledge source.

Allows you to take control over the process of converting text into indexable/searchable tokens.

An object that contains information about the matches that were found, and related metadata.

A complex object that can be used to specify alternative spellings or synonyms to the root entity name.

A skill looks for text from a custom, user-defined list of words and phrases.

The language codes supported for input text by CustomEntityLookupSkill.

Allows you to configure normalization for filterable, sortable, and facetable fields, which by default operate with strict matching.

Base type for data change detection policies.

Base type for data deletion detection policies.

Represents credentials that can be used to connect to a datasource.

An empty object that represents the default Azure AI service resource for a skillset.

Decomposes compound words found in many Germanic languages.

Defines a function that boosts scores based on distance from a geographic location.

Provides parameter values to a distance scoring function.

A skill that extracts content from a file within the enrichment pipeline.

A skill that extracts content and layout information, via Azure AI Services, from files within the enrichment pipeline.

Controls the cardinality for chunking the content.

Controls the cardinality of the chunk unit.

Controls the cardinality of the content extracted from the document by the skill.

The depth of headers in the markdown output.

Controls the cardinality of the output format.

Controls the cardinality of the output produced by the skill.

The type of the keysOrIds.

Generates n-grams of the given size(s) starting from the front or the back of an input token.

Generates n-grams of the given size(s) starting from the front or the back of an input token.

Tokenizes the input from an edge into n-grams of the given size(s).

Removes elisions.

A string indicating what entity categories to return.

Using the Text Analytics API, extracts linked entities from text.

The language codes supported for input text by EntityRecognitionSkill.

Using the Text Analytics API, extracts entities of different types from text.

Contains configuration options specific to the exhaustive KNN algorithm used during querying, which will perform brute-force search across the entire vector index.

Contains the parameters specific to exhaustive KNN algorithm.

Defines a mapping between a field in a data source and a target field in an index.

Represents a function that transforms a value from a data source before indexing.

Defines a function that boosts scores based on the value of a date-time field.

Provides parameter values to a freshness scoring function.

Statistics for a given index.

Defines a data change detection policy that captures changes based on the value of a high water mark column.

Contains configuration options specific to the HNSW approximate nearest neighbors algorithm used during indexing and querying.

Contains the parameters specific to the HNSW algorithm.

A skill that analyzes image files.

The language codes supported for input by ImageAnalysisSkill.

A string indicating which domain-specific details to return.

Defines behavior of the index projections in relation to the rest of the indexer.

Configuration for OneLake knowledge source.

Parameters for OneLake knowledge source.

Specifies the environment in which the indexer should execute.

Represents the result of an individual indexer execution.

Request body for resync indexer operation.

Options with various types of permission data to index.

Represents parameters for indexer execution.

A dictionary of indexer-specific configuration properties.

Represents a schedule for indexer execution.

Input field mapping for a skill.

A token filter that only keeps tokens with text contained in a specified list of words.

A skill that uses text analytics for key phrase extraction.

The language codes supported for input text by KeyPhraseExtractionSkill.

Marks terms as keywords.

Emits the entire input as a single token.

Emits the entire input as a single token.

Represents a knowledge base definition.

Specifies the Azure OpenAI resource used to do query planning.

Specifies the connection parameters for the model to use for query planning.

The AI model to be used for query planning.

Represents a knowledge source definition.

Optional content extraction mode.

The kind of the knowledge source.

Reference to a knowledge source.

The current synchronization status of the knowledge source.

A skill that detects the language of input text and reports a single language code for every document submitted on the request.

Removes words that are too long or too short.

Base type for analyzers.

Defines the names of all text analyzers supported by the search engine.

Base type for normalizers.

Defines the names of all text normalizers supported by the search engine.

Base type for tokenizers.

Defines the names of all tokenizers supported by the search engine.

Limits the number of tokens while indexing.

Response from a List Datasources request.

Response from a List Indexers request.

Response from a list skillset request.

Response from a List SynonymMaps request.

Standard Apache Lucene analyzer; Composed of the standard tokenizer, lowercase filter and stop filter.

Breaks text following the Unicode Text Segmentation rules.

Breaks text following the Unicode Text Segmentation rules.

Defines a function that boosts scores based on the magnitude of a numeric field.

Provides parameter values to a magnitude scoring function.

A character filter that applies mappings defined with the mappings option.

Specifies the max header depth that will be considered while grouping markdown content.

Specifies the submode that will determine whether a markdown file will be parsed into exactly one search document or multiple search documents.

A skill for merging two or more strings into a single unified string, with an optional user-defined delimiter separating each component part.

Divides text using language-specific rules and reduces words to their base forms.

Divides text using language-specific rules.

Generates n-grams of the given size(s).

Generates n-grams of the given size(s).

Tokenizes the input into n-grams of the given size(s).

Defines a data deletion detection policy utilizing Azure Blob Storage's native soft delete feature for deletion detection.

Defines the sequence of characters to use between the lines of text recognized by the OCR skill.

A skill that extracts text from image files.

The language codes supported for input by OcrSkill.

Output field mapping for a skill.

Using the Text Analytics API, extracts personal information from an input text and gives you the option of masking it.

A string indicating what maskingMode to use to mask the personal information detected in the input text.

Tokenizer for path-like hierarchies.

Flexibly separates text into terms via a regular expression pattern.

Uses Java regexes to emit multiple tokens - one for each capture group in one or more patterns.

A character filter that replaces characters in the input string.

A character filter that replaces characters in the input string.

Tokenizer that uses regex pattern matching to construct distinct tokens.

Create tokens for phonetic matches.

Represents score to use for sort order of documents.

Defines a regular expression flag that can be used in the pattern analyzer and pattern tokenizer.

Contains the options for rescoring.

Represents a resource's usage and quota.

Contains configuration options specific to the scalar quantization compression method used during indexing and querying.

Contains the parameters specific to Scalar Quantization.

Base type for functions that can modify document scores during ranking.

Defines parameters for a search index that influence scoring in search queries.

Represents an index alias, which describes a mapping from the alias name to an index.

Represents a field in an index definition, which describes the name, data type, and search behavior of a field.

Defines the data type of a field in a search index.

Represents a search index definition, which describes the fields and search behavior of an index.

Field reference for a search index.

Knowledge Source targeting a search index.

Parameters for search index knowledge source.

Represents a search index definition, which describes the fields and search behavior of an index.

Represents an indexer.

Represents information about the entity (such as Azure SQL table or CosmosDB collection) that will be indexed.

Abstract base type for data identities.

Clears the identity property of a datasource.

Represents a datasource definition, which can be used to configure an indexer.

Defines the type of a datasource.

Specifies the identity for a datasource to use.

Represents an item- or document-level indexing error.

Definition of additional projections to secondary search indexes.

Description for what data to store in the designated search index.

A dictionary of index projection-specific configuration properties.

Definition of additional projections to azure blob, table, or files, of enriched data.

Abstract class to share properties between concrete selectors.

Projection definition for what data to store in Azure Files.

Projection definition for what data to store in Azure Blob.

Container object for various projection selectors.

Abstract class to share properties between concrete selectors.

Description for what data to store in Azure Tables.

Represents the limits that can be applied to an indexer.

Base type for skills.

A list of skills.

Represents the current status and execution history of an indexer.

Represents an item-level warning.

A customer-managed encryption key in Azure Key Vault.

Represents service-level resource counters and quotas.

Represents various service level limits.

Response from a get service statistics request.

Defines how the Suggest API should apply to a group of fields in the index.

Defines a specific configuration to be used in the context of semantic capabilities.

A field that is used as part of the semantic configuration.

Describes the title, content, and keywords fields to be used for semantic ranking, captions, highlights, and answers.

Defines parameters for a search index that influence semantic capabilities.

The language codes supported for input text by SentimentSkill.

Using the Text Analytics API, evaluates unstructured text and for each record, provides sentiment labels (such as "negative", "neutral" and "positive") based on the highest confidence score found by the service at a sentence and document-level.

A skill for reshaping the outputs.

Creates combinations of tokens as a single token.

Base type for similarity algorithms.

The type of the skill names.

A filter that stems words using a Snowball-generated stemmer.

Defines a data deletion detection policy that implements a soft-deletion strategy.

A skill to split a string into chunks of text.

The language codes supported for input text by SplitSkill.

Defines a data change detection policy that captures changes using the Integrated Change Tracking feature of Azure SQL Database.

Provides the ability to override other stemming filters with custom dictionary-based stemming.

Language specific stemming filter.

Divides text at non-letters; Applies the lowercase and stopword token filters.

Removes stop words from a token stream.

Represents a synonym map definition.

Matches single or multi-word synonyms in a token stream.

Defines a function that boosts scores of documents with string values matching a given list of tags.

Provides parameter values to a tag scoring function.

A value indicating which split mode to perform.

A skill to translate text from one language to another.

The language codes supported for input text by TextTranslationSkill.

Defines weights on index fields for which matches should boost scoring in search queries.

Base type for token filters.

Defines the names of all token filters supported by the search engine.

Truncates the terms to a specific length.

Tokenizes urls and emails as one token.

Filters out tokens with same text as the previous token.

The encoding format for interpreting vector field contents.

Contains configuration options related to vector search.

Contains configuration options specific to the algorithm used during indexing or querying.

The algorithm used for indexing and querying.

The similarity metric to use for vector comparisons.

Contains configuration options specific to the compression method used during indexing or querying.

The compression method used for indexing and querying.

The storage method for the original full-precision vectors used for rescoring and internal index operations.

The quantized data type of compressed vector values.

Defines a combination of configurations to use with vector search.

Specifies the vectorization method to be used during query time.

The vectorization method to be used during query time.

The strings indicating what visual feature types to return.

A dictionary of http request headers.

A skill that can call a Web API endpoint, allowing you to extend a skillset by having it call your custom code.

Specifies a user-defined vectorizer for generating the vector embedding of a query string.

Specifies the properties for connecting to a user-defined vectorizer.

Knowledge Source targeting web results.

Configuration for web knowledge source domain.

Domain allow/block configuration for web knowledge source.

Parameters for web knowledge source.

Splits words into subwords and performs optional transformations on subword groups.

Scripts that can be ignored by CjkBigramTokenFilter.

Specifies which side of the input an n-gram should be generated from.

Represents the status of an individual indexer execution.

Represents the overall indexer status.

Lists the languages supported by the Microsoft language stemming tokenizer.

Lists the languages supported by the Microsoft language tokenizer.

Identifies the type of phonetic encoder to use with a PhoneticTokenFilter.

Defines the aggregation function used to combine the results of all the scoring functions in a scoring profile.

Defines the function used to interpolate score boosting across a range of documents.

The language to use for a Snowball token filter.

The language to use for a stemmer token filter.

Identifies a predefined list of language-specific stopwords.

Represents classes of characters on which a token filter can operate.