UNPKG

@langchain/community

Version:
1 lines • 4.17 kB
{"version":3,"file":"turbopuffer.d.ts","names":["DocumentInterface","EmbeddingsInterface","AsyncCaller","AsyncCallerParams","VectorStore","TurbopufferDistanceMetric","TurbopufferFilterType","Array","Record","TurbopufferParams","TurbopufferQueryResult","TurbopufferVectorStore","Promise"],"sources":["../../src/vectorstores/turbopuffer.d.ts"],"sourcesContent":["import { type DocumentInterface } from \"@langchain/core/documents\";\nimport type { EmbeddingsInterface } from \"@langchain/core/embeddings\";\nimport { AsyncCaller, AsyncCallerParams } from \"@langchain/core/utils/async_caller\";\nimport { VectorStore } from \"@langchain/core/vectorstores\";\n/**\n * @deprecated Use `TurbopufferDistanceMetric` from `@langchain/turbopuffer` instead.\n */\nexport type TurbopufferDistanceMetric = \"cosine_distance\" | \"euclidean_squared\";\n/**\n * @deprecated Use `TurbopufferFilter` from `@langchain/turbopuffer` instead.\n */\nexport type TurbopufferFilterType = Record<string, Array<[string, string[] | string]>>;\n/**\n * @deprecated Use `TurbopufferParams` from `@langchain/turbopuffer` instead.\n */\nexport interface TurbopufferParams extends AsyncCallerParams {\n apiKey?: string;\n namespace?: string;\n distanceMetric?: TurbopufferDistanceMetric;\n apiUrl?: string;\n batchSize?: number;\n}\n/**\n * @deprecated Use `@langchain/turbopuffer` instead.\n */\nexport interface TurbopufferQueryResult {\n dist: number;\n id: number;\n vector?: number[];\n attributes: Record<string, string>;\n}\n/**\n * @deprecated Use `TurbopufferVectorStore` from `@langchain/turbopuffer` instead.\n * The new package uses the official SDK and supports document deletion, region\n * configuration, and returns document IDs in search results.\n */\nexport declare class TurbopufferVectorStore extends VectorStore {\n FilterType: TurbopufferFilterType;\n get lc_secrets(): {\n [key: string]: string;\n };\n get lc_aliases(): {\n [key: string]: string;\n };\n static lc_name(): string;\n protected distanceMetric: TurbopufferDistanceMetric;\n protected apiKey: string;\n protected namespace: string;\n protected apiUrl: string;\n caller: AsyncCaller;\n batchSize: number;\n _vectorstoreType(): string;\n constructor(embeddings: EmbeddingsInterface, args: TurbopufferParams);\n defaultHeaders(): {\n Authorization: string;\n \"Content-Type\": string;\n };\n callWithRetry(fetchUrl: string, stringifiedBody: string | undefined, method?: string): Promise<any>;\n addVectors(vectors: number[][], documents: DocumentInterface[], options?: {\n ids?: string[];\n }): Promise<string[]>;\n delete(params: {\n deleteIndex?: boolean;\n }): Promise<void>;\n addDocuments(documents: DocumentInterface[], options?: {\n ids?: string[];\n }): Promise<string[]>;\n protected queryVectors(query: number[], k: number, includeVector?: boolean, filter?: this[\"FilterType\"]): Promise<TurbopufferQueryResult[]>;\n similaritySearchVectorWithScore(query: number[], k: number, filter?: this[\"FilterType\"]): Promise<[DocumentInterface, number][]>;\n static fromDocuments(docs: DocumentInterface[], embeddings: EmbeddingsInterface, dbConfig: TurbopufferParams): Promise<TurbopufferVectorStore>;\n}\n//# sourceMappingURL=turbopuffer.d.ts.map"],"mappings":";;;;;;;;;AAOA;AAIYM,KAJAD,yBAAAA,GAIqB,iBAAS,GAAA,mBAAA;AAI1C;AAUA;AAWA;AACgBC,KA1BJA,qBAAAA,GAAwBE,MA0BpBF,CAAAA,MAAAA,EA1BmCC,KA0BnCD,CAAAA,CAAAA,MAAAA,EAAAA,MAAAA,EAAAA,GAAAA,MAAAA,CAAAA,CAAAA,CAAAA;;;;AAeuCG,UArCtCA,iBAAAA,SAA0BN,iBAqCYM,CAAAA;EAKoCG,MAAAA,CAAAA,EAAAA,MAAAA;EAC5CZ,SAAAA,CAAAA,EAAAA,MAAAA;EAEvCY,cAAAA,CAAAA,EA1CaP,yBA0CbO;EAGAA,MAAAA,CAAAA,EAAAA,MAAAA;EACoBZ,SAAAA,CAAAA,EAAAA,MAAAA;;;;;AAIkEY,UA3C7EF,sBAAAA,CA2C6EE;EAC/DZ,IAAAA,EAAAA,MAAAA;EAAiCC,EAAAA,EAAAA,MAAAA;EAA+BQ,MAAAA,CAAAA,EAAAA,MAAAA,EAAAA;EAA4BE,UAAAA,EAxC3GH,MAwC2GG,CAAAA,MAAAA,EAAAA,MAAAA,CAAAA;;;AAjC5D;;;;cAA1CA,sBAAAA,SAA+BP,WAAAA;cACpCE;;;;;;;;4BAQcD;;;;UAIlBH;;;0BAGgBD,2BAA2BQ;;;;;yFAKoCG;6CAC5CZ;;MAEvCY;;;MAGAA;0BACoBZ;;MAEpBY;4GACsGA,QAAQF;4FACxBE,SAASZ;6BACxEA,iCAAiCC,+BAA+BQ,oBAAoBG,QAAQD"}