@forge-ml/rag
Version:
A RAG (Retrieval-Augmented Generation) package for Forge ML
36 lines (35 loc) • 1.01 kB
TypeScript
import { RedisClientType } from "redis";
import { VectorStore } from "../../../types";
declare class RedisVectorStore implements VectorStore {
client: RedisClientType;
constructor(url: string);
createIndex(): Promise<void>;
addEmbedding(embedding: {
chunkId: string;
documentId: string;
embedding: number[];
}): Promise<"OK" | null>;
storeEmbeddings(embeddings: {
chunkId: string;
documentId: string;
embedding: number[];
}[]): Promise<void>;
queryEmbeddings(query: number[], k: number): Promise<{
chunkId: string;
documentId: string;
score: number;
}[]>;
knnSearchEmbeddings({ inputVector, k, }: {
inputVector: number[];
k: number;
}): Promise<{
total: number;
documents: {
id: string;
value: {
[x: string]: string | number | any | any[] | null;
};
}[];
}>;
}
export default RedisVectorStore;