@juspay/neurolink/dist/lib/evaluation/ragasEvaluator.d.ts

Universal AI Development Platform with working MCP integration, multi-provider support, voice (TTS/STT/realtime), and professional CLI. 58+ external MCP servers discoverable, multimodal file processing, RAG pipelines. Build, test, and deploy AI applicatio

import type { EnhancedEvaluationContext, EvaluationResult, GetPromptFunction } from "../types/index.js";
/**
 * Implements a RAGAS-style evaluator that uses a "judge" LLM to score the
 * quality of an AI response based on rich, contextual information.
 */
export declare class RAGASEvaluator {
    private evaluationModel;
    private providerName;
    private threshold;
    private promptBuilder;
    private promptGenerator?;
    constructor(evaluationModel?: string, providerName?: string, threshold?: number, promptGenerator?: GetPromptFunction);
    /**
     * Evaluates an AI-generated response using a model-based approach.
     *
     * @param context The rich, contextual information for the evaluation.
     * @returns A promise that resolves to a detailed `EvaluationResult`.
     */
    evaluate(context: EnhancedEvaluationContext): Promise<EvaluationResult>;
    /**
     * Parses the raw JSON string from the judge LLM into a structured `EvaluationResult` object.
     * It includes error handling to gracefully manage malformed JSON.
     *
     * @param rawResponse The raw string response from the evaluation model.
     * @returns A structured object containing the evaluation scores and feedback.
     */
    private parseEvaluationResponse;
}