langchain.js
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    Interface for the arguments required to initialize an Azion library.

    interface AzionRetrieverArgs {
        dbName?: string;
        entityExtractor?: any;
        expandedMetadata?: boolean;
        filters?: AzionFilter[];
        ftsK?: number;
        ftsTable?: string;
        maxItemsSearch?: number;
        metadataItems?: string[];
        promptEntityExtractor?: string;
        searchType?: "hybrid" | "similarity";
        similarityK?: number;
        vectorTable?: string;
    }

    Hierarchy (View Summary)

    Index

    Properties

    dbName?: string

    The name of the database to search for documents.

    entityExtractor?: any

    The chatmodel to extract entities to perform Full text search on the database

    expandedMetadata?: boolean

    Whether the metadata is contained in a single column or multiple columns

    filters?: AzionFilter[]

    Filters to apply to the search. Default is an empty array.

    ftsK?: number

    The number of documents retrieved with full text search. Minimum is 1.

    ftsTable?: string

    Name of the table to perform full text search. Default is 'document_fts'

    maxItemsSearch?: number

    Max items to maintain per searchtype. Default is 3.

    metadataItems?: string[]

    The columns from the tables that metadata must contain

    promptEntityExtractor?: string

    The prompt to the chatmodel to extract entities to perform Full text search on the database

    searchType?: "hybrid" | "similarity"

    Search type to perform. Cosine similarity and hybrid (vector + FTS) are currently supported.

    similarityK?: number

    The number of documents retrieved with cosine similarity (vector) search. Minimum is 1.

    vectorTable?: string

    Name of the table to perform vector similarity seach. Default is 'documents'