/**
 * Broad operational-impact estimate for hosted LLM inference.
 *
 * This is deliberately a range, not a meter reading:
 * - 0.3–1.5 J/token covers published H100 inference benchmarks.
 * - 0.27–1.08 L/kWh spans efficient direct cooling and a full-stack
 *   production estimate that also captures associated infrastructure.
 *
 * Model size, batching, context length, hardware, data-centre location and
 * provider efficiency can move the real result outside this band. Local
 * models are included because their token usage still consumes electricity,
 * but Codeep cannot measure the device directly.
 */
export interface ResourceImpactEstimate {
    energyWhLow: number;
    energyWhHigh: number;
    waterMlLow: number;
    waterMlHigh: number;
}
export declare function estimateResourceImpact(totalTokens: number): ResourceImpactEstimate;
export declare function formatResourceImpact(estimate: ResourceImpactEstimate): {
    energy: string;
    water: string;
};
export declare function formatResourceImpactReport(totalTokens: number): string[];