@juspay/neurolink
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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
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JavaScript
/**
* @file Contains the logic for mapping raw evaluation results to the structured EvaluationData type.
*/
import { SpanSerializer, SpanType, SpanStatus, getMetricsAggregator, } from "../observability/index.js";
/**
* Maps a raw `EvaluationResult` to the structured `EvaluationData` format.
* This includes calculating derived fields like `isOffTopic` and `alertSeverity`.
*
* @param result The raw `EvaluationResult` from the evaluator.
* @param threshold The score threshold to determine if the evaluation is passing.
* @param offTopicThreshold The score below which a response is considered off-topic.
* @param highSeverityThreshold The score below which a failing response is high severity.
* @returns A structured `EvaluationData` object.
*/
export function mapToEvaluationData(evalContext, result, threshold, offTopicThreshold = 5, highSeverityThreshold = 4) {
const span = SpanSerializer.createSpan(SpanType.EVALUATION, "evaluation.score", {
"evaluation.dimension": "relevance|accuracy|completeness|overall",
scores: {
relevance: result.relevanceScore,
accuracy: result.accuracyScore,
completeness: result.completenessScore,
overall: result.finalScore,
},
});
const startTime = Date.now();
try {
const isPassing = result.finalScore >= threshold;
const evaluationData = {
relevance: result.relevanceScore,
accuracy: result.accuracyScore,
completeness: result.completenessScore,
overall: result.finalScore,
isOffTopic: result.finalScore < offTopicThreshold,
alertSeverity: isPassing
? "none"
: result.finalScore < highSeverityThreshold
? "high"
: "medium",
reasoning: result.reasoning,
suggestedImprovements: result.suggestedImprovements,
evaluationModel: result.evaluationModel,
evaluationTime: result.evaluationTime,
evaluationAttempt: result.attemptNumber,
responseContent: evalContext.aiResponse,
queryContent: evalContext.userQuery,
};
span.durationMs = Date.now() - startTime;
const endedSpan = SpanSerializer.endSpan(span, SpanStatus.OK);
getMetricsAggregator().recordSpan(endedSpan);
return evaluationData;
}
catch (error) {
span.durationMs = Date.now() - startTime;
const endedSpan = SpanSerializer.endSpan(span, SpanStatus.ERROR);
endedSpan.statusMessage =
error instanceof Error ? error.message : String(error);
getMetricsAggregator().recordSpan(endedSpan);
throw error;
}
}