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‎specification/_types/Retriever.ts

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* specific language governing permissions and limitations
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* under the License.
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*/
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import { QueryVector, QueryVectorBuilder, RescoreVector } from '@_types/Knn'
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import { float, integer } from '@_types/Numeric'
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import { Sort, SortResults } from '@_types/sort'
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import { FieldCollapse } from '@global/search/_types/FieldCollapse'
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import { Rescore } from '@global/search/_types/rescoring'
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import { UserDefinedValue } from '@spec_utils/UserDefinedValue'
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import {Id, IndexName} from './common'
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import { QueryVector, QueryVectorBuilder, RescoreVector } from '@_types/Knn'
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import { float, integer } from '@_types/Numeric'
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import { Sort, SortResults } from '@_types/sort'
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import { Id, IndexName } from './common'
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import { QueryContainer } from './query_dsl/abstractions'
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/**
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* @variants container
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*/
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export class RetrieverContainer {
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/** A retriever that replaces the functionality of a traditional query. */
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standard?: StandardRetriever
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/** A retriever that replaces the functionality of a knn search. */
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knn?: KnnRetriever
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/** A retriever that produces top documents from reciprocal rank fusion (RRF). */
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rrf?: RRFRetriever
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/** A retriever that reranks the top documents based on a reranking model using the InferenceAPI */
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text_similarity_reranker?: TextSimilarityReranker
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/** A retriever that replaces the functionality of a rule query. */
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rule?: RuleRetriever
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/** A retriever that re-scores only the results produced by its child retriever. */
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rescorer?: RescorerRetriever
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/** A retriever that supports the combination of different retrievers through a weighted linear combination. */
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linear?: LinearRetriever
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/**
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* A pinned retriever applies pinned documents to the underlying retriever.
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* This retriever will rewrite to a PinnedQueryBuilder.
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*/
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pinned?: PinnedRetriever
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/** A retriever that replaces the functionality of a traditional query. */
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standard?: StandardRetriever
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/** A retriever that replaces the functionality of a knn search. */
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knn?: KnnRetriever
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/** A retriever that produces top documents from reciprocal rank fusion (RRF). */
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rrf?: RRFRetriever
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/** A retriever that reranks the top documents based on a reranking model using the InferenceAPI */
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text_similarity_reranker?: TextSimilarityReranker
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/** A retriever that replaces the functionality of a rule query. */
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rule?: RuleRetriever
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/** A retriever that re-scores only the results produced by its child retriever. */
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rescorer?: RescorerRetriever
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/** A retriever that supports the combination of different retrievers through a weighted linear combination. */
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linear?: LinearRetriever
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/**
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* A pinned retriever applies pinned documents to the underlying retriever.
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* This retriever will rewrite to a PinnedQueryBuilder.
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*/
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pinned?: PinnedRetriever
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}
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export class RetrieverBase {
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/** Query to filter the documents that can match. */
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filter?: QueryContainer | QueryContainer[]
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/** Minimum _score for matching documents. Documents with a lower _score are not included in the top documents. */
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min_score?: float
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/** Retriever name. */
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_name?: string
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/** Query to filter the documents that can match. */
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filter?: QueryContainer | QueryContainer[]
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/** Minimum _score for matching documents. Documents with a lower _score are not included in the top documents. */
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min_score?: float
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/** Retriever name. */
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_name?: string
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}
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export class RescorerRetriever extends RetrieverBase {
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/** Inner retriever. */
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retriever: RetrieverContainer
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rescore: Rescore | Rescore[]
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/** Inner retriever. */
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retriever: RetrieverContainer
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rescore: Rescore | Rescore[]
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}
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export class LinearRetriever extends RetrieverBase {
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/** Inner retrievers. */
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retrievers?: InnerRetriever[]
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rank_window_size: integer
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/** Inner retrievers. */
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retrievers?: InnerRetriever[]
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rank_window_size: integer
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}
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export class PinnedRetriever extends RetrieverBase {
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/** Inner retriever. */
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retriever: RetrieverContainer
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ids?: string[]
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docs?: SpecifiedDocument[]
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rank_window_size: integer
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/** Inner retriever. */
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retriever: RetrieverContainer
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ids?: string[]
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docs?: SpecifiedDocument[]
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rank_window_size: integer
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}
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export class InnerRetriever {
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retriever: RetrieverContainer
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weight: float
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normalizer: ScoreNormalizer
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retriever: RetrieverContainer
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weight: float
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normalizer: ScoreNormalizer
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}
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export enum ScoreNormalizer {
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none,
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minmax
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none,
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minmax
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}
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export class SpecifiedDocument {
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index?: IndexName
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id: Id
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index?: IndexName
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id: Id
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}
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export class StandardRetriever extends RetrieverBase {
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/** Defines a query to retrieve a set of top documents. */
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query?: QueryContainer
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/** Defines a search after object parameter used for pagination. */
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search_after?: SortResults
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/** Maximum number of documents to collect for each shard. */
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terminate_after?: integer
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/** A sort object that that specifies the order of matching documents. */
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sort?: Sort
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/** Collapses the top documents by a specified key into a single top document per key. */
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collapse?: FieldCollapse
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/** Defines a query to retrieve a set of top documents. */
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query?: QueryContainer
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/** Defines a search after object parameter used for pagination. */
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search_after?: SortResults
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/** Maximum number of documents to collect for each shard. */
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terminate_after?: integer
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/** A sort object that that specifies the order of matching documents. */
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sort?: Sort
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/** Collapses the top documents by a specified key into a single top document per key. */
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collapse?: FieldCollapse
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}
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export class KnnRetriever extends RetrieverBase {
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/** The name of the vector field to search against. */
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field: string
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/** Query vector. Must have the same number of dimensions as the vector field you are searching against. You must provide a query_vector_builder or query_vector, but not both. */
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query_vector?: QueryVector
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/** Defines a model to build a query vector. */
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query_vector_builder?: QueryVectorBuilder
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/** Number of nearest neighbors to return as top hits. */
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k: integer
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/** Number of nearest neighbor candidates to consider per shard. */
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num_candidates: integer
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/** The minimum similarity required for a document to be considered a match. */
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similarity?: float
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/** Apply oversampling and rescoring to quantized vectors
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* @availability stack since=8.18.0
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* @availability serverless
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*/
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rescore_vector?: RescoreVector
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/** The name of the vector field to search against. */
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field: string
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/** Query vector. Must have the same number of dimensions as the vector field you are searching against. You must provide a query_vector_builder or query_vector, but not both. */
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query_vector?: QueryVector
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/** Defines a model to build a query vector. */
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query_vector_builder?: QueryVectorBuilder
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/** Number of nearest neighbors to return as top hits. */
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k: integer
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/** Number of nearest neighbor candidates to consider per shard. */
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num_candidates: integer
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/** The minimum similarity required for a document to be considered a match. */
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similarity?: float
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/** Apply oversampling and rescoring to quantized vectors
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* @availability stack since=8.18.0
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* @availability serverless
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*/
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rescore_vector?: RescoreVector
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}
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export class RRFRetriever extends RetrieverBase {
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/** A list of child retrievers to specify which sets of returned top documents will have the RRF formula applied to them. */
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retrievers: RetrieverContainer[]
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/** This value determines how much influence documents in individual result sets per query have over the final ranked result set. */
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rank_constant?: integer
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/** This value determines the size of the individual result sets per query. */
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rank_window_size?: integer
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/** A list of child retrievers to specify which sets of returned top documents will have the RRF formula applied to them. */
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retrievers: RetrieverContainer[]
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/** This value determines how much influence documents in individual result sets per query have over the final ranked result set. */
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rank_constant?: integer
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/** This value determines the size of the individual result sets per query. */
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rank_window_size?: integer
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}
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export class TextSimilarityReranker extends RetrieverBase {
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/** The nested retriever which will produce the first-level results, that will later be used for reranking. */
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retriever: RetrieverContainer
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/** This value determines how many documents we will consider from the nested retriever. */
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rank_window_size?: integer
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/** Unique identifier of the inference endpoint created using the inference API. */
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inference_id?: string
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/** The text snippet used as the basis for similarity comparison */
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inference_text?: string
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/** The document field to be used for text similarity comparisons. This field should contain the text that will be evaluated against the inference_text */
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field?: string
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/** The nested retriever which will produce the first-level results, that will later be used for reranking. */
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retriever: RetrieverContainer
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/** This value determines how many documents we will consider from the nested retriever. */
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rank_window_size?: integer
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/** Unique identifier of the inference endpoint created using the inference API. */
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inference_id?: string
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/** The text snippet used as the basis for similarity comparison */
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inference_text?: string
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/** The document field to be used for text similarity comparisons. This field should contain the text that will be evaluated against the inference_text */
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field?: string
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}
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export class RuleRetriever extends RetrieverBase {
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/** The ruleset IDs containing the rules this retriever is evaluating against. */
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ruleset_ids: Id | Id[]
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/** The match criteria that will determine if a rule in the provided rulesets should be applied. */
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match_criteria: UserDefinedValue
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/** The retriever whose results rules should be applied to. */
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retriever: RetrieverContainer
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/** This value determines the size of the individual result set. */
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rank_window_size?: integer
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/** The ruleset IDs containing the rules this retriever is evaluating against. */
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ruleset_ids: Id | Id[]
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/** The match criteria that will determine if a rule in the provided rulesets should be applied. */
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match_criteria: UserDefinedValue
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/** The retriever whose results rules should be applied to. */
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retriever: RetrieverContainer
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/** This value determines the size of the individual result set. */
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rank_window_size?: integer
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}

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