46 lines
1.7 KiB
TypeScript
46 lines
1.7 KiB
TypeScript
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import { BaseRetriever, type BaseRetrieverInput } from "@langchain/core/retrievers";
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import type { VectorStoreInterface } from "@langchain/core/vectorstores";
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import { Document } from "@langchain/core/documents";
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import { BaseStore, type BaseStoreInterface } from "@langchain/core/stores";
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/**
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* Arguments for the MultiVectorRetriever class.
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*/
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export interface MultiVectorRetrieverInput extends BaseRetrieverInput {
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vectorstore: VectorStoreInterface;
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/** @deprecated Prefer `byteStore`. */
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docstore?: BaseStoreInterface<string, Document>;
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byteStore?: BaseStore<string, Uint8Array>;
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idKey?: string;
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childK?: number;
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parentK?: number;
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}
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/**
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* A retriever that retrieves documents from a vector store and a document
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* store. It uses the vector store to find relevant documents based on a
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* query, and then retrieves the full documents from the document store.
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* @example
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* ```typescript
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* const retriever = new MultiVectorRetriever({
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* vectorstore: new FaissStore(),
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* byteStore: new InMemoryStore<Unit8Array>(),
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* idKey: "doc_id",
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* childK: 20,
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* parentK: 5,
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* });
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*
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* const retrieverResult = await retriever.getRelevantDocuments("justice breyer");
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* console.log(retrieverResult[0].pageContent.length);
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* ```
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*/
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export declare class MultiVectorRetriever extends BaseRetriever {
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static lc_name(): string;
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lc_namespace: string[];
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vectorstore: VectorStoreInterface;
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docstore: BaseStoreInterface<string, Document>;
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protected idKey: string;
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protected childK?: number;
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protected parentK?: number;
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constructor(args: MultiVectorRetrieverInput);
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_getRelevantDocuments(query: string): Promise<Document[]>;
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}
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