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{"version":3,"file":"singlestore.d.ts","names":["Pool","PoolOptions","EmbeddingsInterface","VectorStore","Document","DocumentInterface","Callbacks","Metadata","Record","DistanceMetrics","SearchStrategy","ConnectionOptions","ConnectionWithUri","ConnectionWithOptions","ConnectionConfig","SearchConfig","SingleStoreVectorStoreConfig","SingleStoreVectorStore","Promise"],"sources":["../../src/vectorstores/singlestore.d.ts"],"sourcesContent":["import type { Pool, PoolOptions } from \"mysql2/promise\";\nimport type { EmbeddingsInterface } from \"@langchain/core/embeddings\";\nimport { VectorStore } from \"@langchain/core/vectorstores\";\nimport { Document, DocumentInterface } from \"@langchain/core/documents\";\nimport { Callbacks } from \"@langchain/core/callbacks/manager\";\nexport type Metadata = Record<string, any>;\nexport type DistanceMetrics = \"DOT_PRODUCT\" | \"EUCLIDEAN_DISTANCE\";\nexport type SearchStrategy = \"VECTOR_ONLY\" | \"TEXT_ONLY\" | \"FILTER_BY_TEXT\" | \"FILTER_BY_VECTOR\" | \"WEIGHTED_SUM\";\nexport interface ConnectionOptions extends PoolOptions {\n}\ntype ConnectionWithUri = {\n connectionOptions?: never;\n connectionURI: string;\n};\ntype ConnectionWithOptions = {\n connectionURI?: never;\n connectionOptions: ConnectionOptions;\n};\ntype ConnectionConfig = ConnectionWithUri | ConnectionWithOptions;\ntype SearchConfig = {\n searchStrategy?: SearchStrategy;\n filterThreshold?: number;\n textWeight?: number;\n vectorWeight?: number;\n vectorselectCountMultiplier?: number;\n};\nexport type SingleStoreVectorStoreConfig = ConnectionConfig & {\n tableName?: string;\n idColumnName?: string;\n contentColumnName?: string;\n vectorColumnName?: string;\n metadataColumnName?: string;\n distanceMetric?: DistanceMetrics;\n useVectorIndex?: boolean;\n vectorIndexName?: string;\n vectorIndexOptions?: Metadata;\n vectorSize?: number;\n useFullTextIndex?: boolean;\n searchConfig?: SearchConfig;\n};\n/**\n * Class for interacting with SingleStoreDB, a high-performance\n * distributed SQL database. It provides vector storage and vector\n * functions.\n */\nexport declare class SingleStoreVectorStore extends VectorStore {\n connectionPool: Pool;\n tableName: string;\n idColumnName: string;\n contentColumnName: string;\n vectorColumnName: string;\n metadataColumnName: string;\n distanceMetric: DistanceMetrics;\n useVectorIndex: boolean;\n vectorIndexName: string;\n vectorIndexOptions: Metadata;\n vectorSize: number;\n useFullTextIndex: boolean;\n searchConfig: SearchConfig;\n _vectorstoreType(): string;\n constructor(embeddings: EmbeddingsInterface, config: SingleStoreVectorStoreConfig);\n /**\n * Creates a new table in the SingleStoreDB database if it does not\n * already exist.\n */\n createTableIfNotExists(): Promise<void>;\n /**\n * Ends the connection to the SingleStoreDB database.\n */\n end(): Promise<void>;\n /**\n * Sets the search configuration for the SingleStoreVectorStore instance.\n * @param config A SearchConfig object.\n */\n setSearchConfig(config: SearchConfig): Promise<void>;\n /**\n * Adds new documents to the SingleStoreDB database.\n * @param documents An array of Document objects.\n */\n addDocuments(documents: Document[]): Promise<void>;\n /**\n * Adds new vectors to the SingleStoreDB database.\n * @param vectors An array of vectors.\n * @param documents An array of Document objects.\n */\n addVectors(vectors: number[][], documents: Document[]): Promise<void>;\n /**\n *\n * Performs a similarity search on the texts stored in the SingleStoreDB\n * using the specified search strategy and distance metric.\n * @param query A string representing the query text.\n * @param vector An array of numbers representing the query vector.\n * @param k The number of nearest neighbors to return.\n * @param filter Optional metadata to filter the texts by.\n * @returns Top matching documents with score\n */\n similaritySearchTextAndVectorWithScore(query: string, vector: number[], k: number, filter?: Metadata): Promise<[Document, number][]>;\n /**\n * Performs a similarity search on the texts stored in the SingleStoreDB\n * @param query A string representing the query text.\n * @param k The number of nearest neighbors to return. By default, it is 4.\n * @param filter Optional metadata to filter the texts by.\n * @param _callbacks - Callbacks object, not used in this implementation.\n * @returns Top matching documents\n */\n similaritySearch(query: string, k?: number, filter?: Metadata, _callbacks?: Callbacks | undefined): Promise<DocumentInterface<Metadata>[]>;\n /**\n * Performs a similarity search on the texts stored in the SingleStoreDB\n * @param query A string representing the query text.\n * @param k The number of nearest neighbors to return. By default, it is 4.\n * @param filter Optional metadata to filter the texts by.\n * @param _callbacks\n * @returns Top matching documents with score\n */\n similaritySearchWithScore(query: string, k?: number, filter?: Metadata, _callbacks?: Callbacks | undefined): Promise<[DocumentInterface<Metadata>, number][]>;\n /**\n * Performs a similarity search on the vectors stored in the SingleStoreDB\n * database.\n * @param query An array of numbers representing the query vector.\n * @param k The number of nearest neighbors to return.\n * @param filter Optional metadata to filter the vectors by.\n * @returns Top matching vectors with score\n */\n similaritySearchVectorWithScore(query: number[], k: number, filter?: Metadata): Promise<[Document, number][]>;\n /**\n * Creates a new instance of the SingleStoreVectorStore class from a list\n * of texts.\n * @param texts An array of strings.\n * @param metadatas An array of metadata objects.\n * @param embeddings An Embeddings object.\n * @param dbConfig A SingleStoreVectorStoreConfig object.\n * @returns A new SingleStoreVectorStore instance\n */\n static fromTexts(texts: string[], metadatas: object[], embeddings: EmbeddingsInterface, dbConfig: SingleStoreVectorStoreConfig): Promise<SingleStoreVectorStore>;\n /**\n * Creates a new instance of the SingleStoreVectorStore class from a list\n * of Document objects.\n * @param docs An array of Document objects.\n * @param embeddings An Embeddings object.\n * @param dbConfig A SingleStoreVectorStoreConfig object.\n * @returns A new SingleStoreVectorStore instance\n */\n static fromDocuments(docs: Document[], embeddings: EmbeddingsInterface, dbConfig: SingleStoreVectorStoreConfig): Promise<SingleStoreVectorStore>;\n}\nexport {};\n//# sourceMappingURL=singlestore.d.ts.map"],"mappings":";;;;;;;KAKYO,QAAAA,GAAWC;KACXC,eAAAA;AADAF,KAEAG,cAAAA,GAFWF,aAAM,GAAA,WAAA,GAAA,gBAAA,GAAA,kBAAA,GAAA,cAAA;AACjBC,UAEKE,iBAAAA,SAA0BV,WAFhB,CAAA,CAC3B;AACA,KAEKW,iBAAAA,GAF6B;EAE7BA,iBAAAA,CAAAA,EAAiB,KAAA;EAIjBC,aAAAA,EAAAA,MAAAA;AAEmC,CAAA;AAEyB,KAJ5DA,qBAAAA,GAKY;EAOLG,aAAAA,CAAAA,EAAAA,KAAAA;EAA+BF,iBAAAA,EAVpBH,iBAUoBG;CAMtBL;KAdhBK,gBAAAA,GAAmBF,iBAiBCL,GAjBmBM,qBAiBnBN;KAhBpBQ,YAAAA,GAmBcA;EAAY,cAAA,CAAA,EAlBVL,cAkBU;EAOVO,eAAAA,CAAAA,EAAAA,MAAAA;EACDjB,UAAAA,CAAAA,EAAAA,MAAAA;EAMAS,YAAAA,CAAAA,EAAAA,MAAAA;EAGIF,2BAAAA,CAAAA,EAAAA,MAAAA;CAGNQ;AAEUb,KAlChBc,4BAAAA,GAA+BF,gBAkCfZ,GAAAA;EAA6Bc,SAAAA,CAAAA,EAAAA,MAAAA;EAK3BE,YAAAA,CAAAA,EAAAA,MAAAA;EAInBA,iBAAAA,CAAAA,EAAAA,MAAAA;EAKiBH,gBAAAA,CAAAA,EAAAA,MAAAA;EAAeG,kBAAAA,CAAAA,EAAAA,MAAAA;EAKfd,cAAAA,CAAAA,EA/CPK,eA+COL;EAAac,cAAAA,CAAAA,EAAAA,OAAAA;EAMMd,eAAAA,CAAAA,EAAAA,MAAAA;EAAac,kBAAAA,CAAAA,EAlDnCX,QAkDmCW;EAWoCX,UAAAA,CAAAA,EAAAA,MAAAA;EAAoBH,gBAAAA,CAAAA,EAAAA,OAAAA;EAATc,YAAAA,CAAAA,EA1DxFH,YA0DwFG;CASlDX;;;;;;AASgCD,cArEpEW,sBAAAA,SAA+Bd,WAAAA,CAqEqCG;EAAmDC,cAAAA,EApExHP,IAoEwHO;EAAlBF,SAAAA,EAAAA,MAAAA;EAATa,YAAAA,EAAAA,MAAAA;EASxCX,iBAAAA,EAAAA,MAAAA;EAAoBH,gBAAAA,EAAAA,MAAAA;EAATc,kBAAAA,EAAAA,MAAAA;EAUbhB,cAAAA,EAjFnDO,eAiFmDP;EAA+Bc,cAAAA,EAAAA,OAAAA;EAAuCC,eAAAA,EAAAA,MAAAA;EAARC,kBAAAA,EA9E7GX,QA8E6GW;EAStGd,UAAAA,EAAAA,MAAAA;EAAwBF,gBAAAA,EAAAA,OAAAA;EAA+Bc,YAAAA,EApFpED,YAoFoEC;EAAuCC,gBAAAA,CAAAA,CAAAA,EAAAA,MAAAA;EAARC,WAAAA,CAAAA,UAAAA,EAlFzFhB,mBAkFyFgB,EAAAA,MAAAA,EAlF5DF,4BAkF4DE;EAjGjEf;AAAW;;;4BAoBjCe;;;;SAInBA;;;;;0BAKiBH,eAAeG;;;;;0BAKfd,aAAac;;;;;;6CAMMd,aAAac;;;;;;;;;;;8FAWoCX,WAAWW,SAASd;;;;;;;;;uDAS3DG,uBAAuBD,wBAAwBY,QAAQb,kBAAkBE;;;;;;;;;gEAShEA,uBAAuBD,wBAAwBY,SAASb,kBAAkBE;;;;;;;;;uEASnEA,WAAWW,SAASd;;;;;;;;;;qEAUtBF,+BAA+Bc,+BAA+BE,QAAQD;;;;;;;;;6BAS9Gb,wBAAwBF,+BAA+Bc,+BAA+BE,QAAQD"}