@bobmatnyc/ai-code-review/dist/estimators/openRouterEstimator.d.ts

A TypeScript-based tool for automated code reviews using AI models from Google Gemini, Anthropic Claude, and OpenRouter

/**
 * @fileoverview OpenRouter-specific token and cost estimator.
 *
 * This module provides token counting and cost estimation specifically
 * for models available through OpenRouter, with accurate pricing information.
 */
import { AbstractTokenEstimator } from './abstractEstimator';
/**
 * OpenRouter-specific token and cost estimator
 */
export declare class OpenRouterTokenEstimator extends AbstractTokenEstimator {
    private static instance;
    private anthropicEstimator;
    private openaiEstimator;
    /**
     * Get the singleton instance of the estimator
     * @returns OpenRouterTokenEstimator instance
     */
    static getInstance(): OpenRouterTokenEstimator;
    /**
     * Pricing information for OpenRouter-specific models
     * Note: Many models are provided by other providers and use their pricing
     */
    private MODEL_PRICING;
    /**
     * Private constructor to enforce singleton pattern
     */
    private constructor();
    /**
     * Get the pricing for a specific model
     * @param modelName Name of the model
     * @returns Pricing information for the model
     */
    private getModelPricing;
    /**
     * Calculate the cost for a given number of input and output tokens
     * @param inputTokens Number of input tokens
     * @param outputTokens Number of output tokens
     * @param modelName Name of the model (optional, uses default if not provided)
     * @returns Estimated cost in USD
     */
    calculateCost(inputTokens: number, outputTokens: number, modelName?: string): number;
    /**
     * Get the default model name for this estimator
     * @returns Default model name
     */
    getDefaultModel(): string;
    /**
     * Check if this estimator supports a given model
     * @param modelName Name of the model to check
     * @returns True if the model is supported, false otherwise
     */
    supportsModel(modelName: string): boolean;
}