import { DocumentByInfo, FieldPaths, FilterExpression, FunctionReference, GenericActionCtx, GenericDataModel, GenericTableInfo, NamedTableInfo, NamedVectorIndex, TableNamesInDataModel, VectorFilterBuilder, VectorIndexNames } from "convex/server";
import type { EmbeddingsInterface } from "@langchain/core/embeddings";
import { VectorStore } from "@langchain/core/vectorstores";
import { Document } from "@langchain/core/documents";
/**
 * Type that defines the config required to initialize the
 * ConvexVectorStore class. It includes the table name,
 * index name, text field name, and embedding field name.
 */
export type ConvexVectorStoreConfig<DataModel extends GenericDataModel, TableName extends TableNamesInDataModel<DataModel>, IndexName extends VectorIndexNames<NamedTableInfo<DataModel, TableName>>, TextFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, EmbeddingFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, MetadataFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, InsertMutation extends FunctionReference<"mutation", "internal", {
    table: string;
    document: object;
}>, GetQuery extends FunctionReference<"query", "internal", {
    id: string;
}, object | null>> = {
    readonly ctx: GenericActionCtx<DataModel>;
    /**
     * Defaults to "documents"
     */
    readonly table?: TableName;
    /**
     * Defaults to "byEmbedding"
     */
    readonly index?: IndexName;
    /**
     * Defaults to "text"
     */
    readonly textField?: TextFieldName;
    /**
     * Defaults to "embedding"
     */
    readonly embeddingField?: EmbeddingFieldName;
    /**
     * Defaults to "metadata"
     */
    readonly metadataField?: MetadataFieldName;
    /**
     * Defaults to `internal.langchain.db.insert`
     */
    readonly insert?: InsertMutation;
    /**
     * Defaults to `internal.langchain.db.get`
     */
    readonly get?: GetQuery;
};
/**
 * Class that is a wrapper around Convex storage and vector search. It is used
 * to insert embeddings in Convex documents with a vector search index,
 * and perform a vector search on them.
 *
 * ConvexVectorStore does NOT implement maxMarginalRelevanceSearch.
 */
export declare class ConvexVectorStore<DataModel extends GenericDataModel, TableName extends TableNamesInDataModel<DataModel>, IndexName extends VectorIndexNames<NamedTableInfo<DataModel, TableName>>, TextFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, EmbeddingFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, MetadataFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, InsertMutation extends FunctionReference<"mutation", "internal", {
    table: string;
    document: object;
}>, GetQuery extends FunctionReference<"query", "internal", {
    id: string;
}, object | null>> extends VectorStore {
    /**
     * Type that defines the filter used in the
     * similaritySearchVectorWithScore and maxMarginalRelevanceSearch methods.
     * It includes limit, filter and a flag to include embeddings.
     */
    FilterType: {
        filter?: (q: VectorFilterBuilder<DocumentByInfo<GenericTableInfo>, NamedVectorIndex<NamedTableInfo<DataModel, TableName>, IndexName>>) => FilterExpression<boolean>;
        includeEmbeddings?: boolean;
    };
    private readonly ctx;
    private readonly table;
    private readonly index;
    private readonly textField;
    private readonly embeddingField;
    private readonly metadataField;
    private readonly insert;
    private readonly get;
    _vectorstoreType(): string;
    constructor(embeddings: EmbeddingsInterface, config: ConvexVectorStoreConfig<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>);
    /**
     * Add vectors and their corresponding documents to the Convex table.
     * @param vectors Vectors to be added.
     * @param documents Corresponding documents to be added.
     * @returns Promise that resolves when the vectors and documents have been added.
     */
    addVectors(vectors: number[][], documents: Document[]): Promise<void>;
    /**
     * Add documents to the Convex table. It first converts
     * the documents to vectors using the embeddings and then calls the
     * addVectors method.
     * @param documents Documents to be added.
     * @returns Promise that resolves when the documents have been added.
     */
    addDocuments(documents: Document[]): Promise<void>;
    /**
     * Similarity search on the vectors stored in the
     * Convex table. It returns a list of documents and their
     * corresponding similarity scores.
     * @param query Query vector for the similarity search.
     * @param k Number of nearest neighbors to return.
     * @param filter Optional filter to be applied.
     * @returns Promise that resolves to a list of documents and their corresponding similarity scores.
     */
    similaritySearchVectorWithScore(query: number[], k: number, filter?: this["FilterType"]): Promise<[Document, number][]>;
    /**
     * Static method to create an instance of ConvexVectorStore from a
     * list of texts. It first converts the texts to vectors and then adds
     * them to the Convex table.
     * @param texts List of texts to be converted to vectors.
     * @param metadatas Metadata for the texts.
     * @param embeddings Embeddings to be used for conversion.
     * @param dbConfig Database configuration for Convex.
     * @returns Promise that resolves to a new instance of ConvexVectorStore.
     */
    static fromTexts<DataModel extends GenericDataModel, TableName extends TableNamesInDataModel<DataModel>, IndexName extends VectorIndexNames<NamedTableInfo<DataModel, TableName>>, TextFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, EmbeddingFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, MetadataFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, InsertMutation extends FunctionReference<"mutation", "internal", {
        table: string;
        document: object;
    }>, GetQuery extends FunctionReference<"query", "internal", {
        id: string;
    }, object | null>>(texts: string[], metadatas: object[] | object, embeddings: EmbeddingsInterface, dbConfig: ConvexVectorStoreConfig<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>): Promise<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>;
    /**
     * Static method to create an instance of ConvexVectorStore from a
     * list of documents. It first converts the documents to vectors and then
     * adds them to the Convex table.
     * @param docs List of documents to be converted to vectors.
     * @param embeddings Embeddings to be used for conversion.
     * @param dbConfig Database configuration for Convex.
     * @returns Promise that resolves to a new instance of ConvexVectorStore.
     */
    static fromDocuments<DataModel extends GenericDataModel, TableName extends TableNamesInDataModel<DataModel>, IndexName extends VectorIndexNames<NamedTableInfo<DataModel, TableName>>, TextFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, EmbeddingFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, MetadataFieldName extends FieldPaths<NamedTableInfo<DataModel, TableName>>, InsertMutation extends FunctionReference<"mutation", "internal", {
        table: string;
        document: object;
    }>, GetQuery extends FunctionReference<"query", "internal", {
        id: string;
    }, object | null>>(docs: Document[], embeddings: EmbeddingsInterface, dbConfig: ConvexVectorStoreConfig<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>): Promise<ConvexVectorStore<DataModel, TableName, IndexName, TextFieldName, EmbeddingFieldName, MetadataFieldName, InsertMutation, GetQuery>>;
}