sentence2simvecjs/dist/shared/corpusManager.d.ts

Vector-based sentence similarity (0.0-1.0) + embedding export. JavaScript implementation inspired by PINTO0309/sentence2simvec

export interface CorpusItem {
    id: string;
    text: string;
    metadata?: any;
}
export interface CorpusSearchResult {
    item: CorpusItem;
    similarity: number;
    method: 'dice' | 'embedding';
}
export interface CorpusOptions {
    enableDiceCache?: boolean;
    enableEmbeddingCache?: boolean;
    cacheDir?: string;
    persistCache?: boolean;
}
export declare class CorpusManager {
    private corpus;
    private embeddingCache;
    private diceNGramCache;
    private options;
    constructor(options?: CorpusOptions);
    addItem(text: string, id?: string, metadata?: any): Promise<CorpusItem>;
    addItems(items: Array<{
        text: string;
        id?: string;
        metadata?: any;
    }>): Promise<CorpusItem[]>;
    loadFromFile(filePath: string, format?: 'text' | 'json'): Promise<CorpusItem[]>;
    searchByDice(query: string, topK?: number, threshold?: number, ngramSize?: number): Promise<CorpusSearchResult[]>;
    searchByEmbedding(query: string, topK?: number, threshold?: number): Promise<CorpusSearchResult[]>;
    search(query: string, method?: 'dice' | 'embedding' | 'both', topK?: number, threshold?: number): Promise<CorpusSearchResult[]>;
    batchSimilarity(query: string, method?: 'dice' | 'embedding'): Promise<Map<string, number>>;
    getItem(id: string): CorpusItem | undefined;
    getAllItems(): CorpusItem[];
    size(): number;
    clear(): void;
    exportCorpus(filePath: string): Promise<void>;
    exportEmbeddings(filePath: string): Promise<void>;
    private generateId;
}
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