@llm-tools/embedjs/src/store/memory-store.d.ts

A NodeJS RAG framework to easily work with LLMs and custom datasets

import { BaseStore, Conversation, LoaderListEntry, Message } from '@llm-tools/embedjs-interfaces';
export declare class MemoryStore implements BaseStore {
    private loaderCustomValues;
    private loaderCustomValuesMap;
    private loaderList;
    private conversations;
    init(): Promise<void>;
    addLoaderMetadata(loaderId: string, value: LoaderListEntry): Promise<void>;
    getLoaderMetadata(loaderId: string): Promise<LoaderListEntry>;
    hasLoaderMetadata(loaderId: string): Promise<boolean>;
    getAllLoaderMetadata(): Promise<LoaderListEntry[]>;
    loaderCustomSet<T extends Record<string, unknown>>(loaderId: string, key: string, value: T): Promise<void>;
    loaderCustomGet<T extends Record<string, unknown>>(key: string): Promise<T>;
    loaderCustomHas(key: string): Promise<boolean>;
    loaderCustomDelete(key: string): Promise<void>;
    deleteLoaderMetadataAndCustomValues(loaderId: string): Promise<void>;
    addConversation(conversationId: string): Promise<void>;
    getConversation(conversationId: string): Promise<Conversation>;
    hasConversation(conversationId: string): Promise<boolean>;
    deleteConversation(conversationId: string): Promise<void>;
    addEntryToConversation(conversationId: string, entry: Message): Promise<void>;
    clearConversations(): Promise<void>;
}