/**
 * @fileoverview Runtime utilities for React components providing access to MemberJunction core functionality
 * @module @memberjunction/ng-react/utilities
 */
import { IMetadataProvider } from '@memberjunction/core';
import { ComponentUtilities } from '@memberjunction/interactive-component-types';
/**
 * Base class for providing runtime utilities to React components in Angular.
 * This class can be extended and registered with MJ's ClassFactory
 * to provide custom implementations of data access methods.
 */
export declare class RuntimeUtilities {
    private debug;
    /**
     * The provider every read in the built utilities goes through. Always set by
     * {@link buildUtilities} before use — falls back to the global provider there
     * (`provider ?? Metadata.Provider`) when the host doesn't supply one.
     */
    private provider;
    /**
     * Builds the complete utilities object for React components
     * This is the main method that components will use
     *
     * @param provider the host's provider. A React component mounted under a non-default provider
     *        passes its own `ProviderToUse`; omitting it falls back to the global default, named
     *        explicitly rather than reached for via `new Metadata()`.
     */
    buildUtilities(debug?: boolean, provider?: IMetadataProvider): ComponentUtilities;
    /**
     * Sets up the utilities object - copied from skip-chat implementation
     */
    private SetupUtilities;
    private CreateSimpleAITools;
    /**
     * Creates the ML tools surface for components — listing trained models and scoring records.
     * `listModels` reads the `MJ: ML Models` catalog via RunView; `score` marshals the
     * `PredictiveStudio.ScoreRecordSet` Remote Operation over GraphQL to the server engine (the
     * Python sidecar lives server-side and cannot run in the browser). Returns `undefined` when no
     * GraphQL provider is available, so the `ml` capability degrades cleanly.
     */
    private CreateSimpleMLTools;
    /**
     * Loads the trained-model catalog from `MJ: ML Models`, newest version first, mapping each row
     * to a {@link SimpleMLModelInfo}. Resilient — logs and returns `[]` on any failure.
     */
    private listMLModels;
    /**
     * Builds the ExtraFilter clause for {@link listMLModels}. Defaults to `Status='Published'` so
     * components only see promoted models unless the caller overrides the status.
     */
    private buildMLModelsFilter;
    /** Maps a single `MJ: ML Models` row to the component-facing {@link SimpleMLModelInfo} shape. */
    private mapMLModel;
    /** Defensively parses a JSON metrics blob; returns `undefined` for null/empty/invalid JSON. */
    private parseMLMetrics;
    /**
     * Scores records with a trained model by invoking the `PredictiveStudio.ScoreRecordSet` Remote
     * Operation. Normalizes `records` to primary-key strings, requests ephemeral predictions (no
     * write-back), and maps the result. Resilient — logs and returns a zeroed result with the input
     * records counted as failed on any error.
     */
    private scoreMLRecords;
    /**
     * Normalizes a mixed array of primary-key strings and row objects into an array of primary-key
     * strings, reading `primaryKeyField` from objects. Drops entries without a resolvable key.
     */
    private normalizeRecordKeys;
    /** Escapes single quotes for safe inlining into a RunView ExtraFilter SQL string literal. */
    private escapeSqlLiteral;
    private CreateSimpleMetadata;
    private CreateSimpleGeoDataEngine;
    private CreateSimpleRunQuery;
    private CreateSimpleRunView;
}
/**
 * Factory function to create RuntimeUtilities
 * In a Node.js environment, this will use MJ's ClassFactory for runtime substitution
 * In a browser environment, it will use the base class directly
 */
export declare function createRuntimeUtilities(): RuntimeUtilities;