/**
 * VectorStore manages the ChromaDB client and collection for semantic caching.
 * It provides methods to insert task vectors and search for similar tasks.
 */
export declare class VectorStore {
    private client;
    private collection;
    private collectionName;
    private isInitialized;
    constructor(collectionName?: string, chromaUrl?: string);
    /**
     * Initialize the ChromaDB collection.
     * Creates a new collection if it doesn't exist.
     */
    initialize(): Promise<void>;
    /**
     * Insert a task vector with its result into the collection.
     *
     * @param taskId - Unique identifier for the task
     * @param embedding - Vector embedding of the task
     * @param taskDescription - Original task description
     * @param result - Cached result to return on cache hit
     * @param metadata - Additional metadata (agent, timestamp, etc.)
     */
    insertVector(taskId: string, embedding: number[], taskDescription: string, result: any, metadata?: Record<string, any>): Promise<void>;
    /**
     * Search for similar tasks using semantic similarity.
     *
     * @param queryEmbedding - Vector embedding of the query task
     * @param threshold - Minimum similarity score (0-1, default 0.95)
     * @param topK - Number of results to return (default 1)
     * @returns Array of similar tasks with their results and similarity scores
     */
    searchSimilar(queryEmbedding: number[], threshold?: number, topK?: number): Promise<Array<{
        id: string;
        similarity: number;
        result: any;
        taskDescription: string;
        metadata: Record<string, any>;
    }>>;
    /**
     * Get the total count of cached tasks.
     */
    getCount(): Promise<number>;
    /**
     * Clear all cached tasks from the collection.
     */
    clear(): Promise<void>;
    /**
     * Check if the VectorStore is ready to use.
     */
    isReady(): boolean;
}
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