import { GenerativeAIJobType } from '../../GenerativeAIJobType';
import { IGenerativeAIJobResult } from '../../job/GenerativeAIJobResult';
import { ISearchResult } from '../../search';
import { PromptTypeText, PromptTypeVector } from './result';
/**
 * The AI prompt result Interface
 * Represents the result of an AI prompt.
 * @category AI
 */
export interface IGenerativeAIPromptResult extends IGenerativeAIJobResult {
    /**
     * The prompt AI job type.
     */
    type: GenerativeAIJobType.Prompt | GenerativeAIJobType.Inference | GenerativeAIJobType.Embed;
    /**
     * The output of the AI job.
     */
    output?: PromptTypeText | PromptTypeVector;
    /**
     * The relevant context used by the AI job.
     */
    context?: ISearchResult[];
    /**
     * The internal context used by the AI job.
     */
    internalContext?: {
        [key: string]: string;
    };
    /**
     * The file generated by the AI job.
     */
    resultFile?: string;
    /**
     * The tokens used by the AI job.
     */
    inputTokens?: number;
    /**
     * The tokens generated by the AI job.
     */
    outputTokens?: number;
    /**
     * The tokens used by the AI job, bucketed by type for billing. `base` holds
     * tokens billed at the model's list price; other buckets (cacheRead,
     * cacheWrite5m, cacheWrite1h, cached, audio, image, …) are converted to
     * base-token equivalents at billing time via the model's tokenRates.
     * Optional: connectors without per-type usage data keep reporting only the
     * flat inputTokens/outputTokens counts.
     */
    tokenBuckets?: {
        input?: Record<string, number>;
        output?: Record<string, number>;
    };
}