@arizeai/phoenix-evals/dist/esm/llm/createDocumentRelevancyEvaluator.js

A library for running evaluations for AI use cases

import { createClassifier } from "./createClassifier.js";
import { DOCUMENT_RELEVANCY_TEMPLATE, DOCUMENT_RELEVANCY_CHOICES, } from "../default_templates/DOCUMENT_RELEVANCY_TEMPLATE.js";
/**
 * Creates a document relevancy evaluator function.
 *
 * This function returns an evaluator that determines whether a given document text
 * is relevant to a provided input question. The evaluator uses a classification model
 * and a prompt template to make its determination.
 *
 * @param args - The arguments for creating the document relevancy evaluator.
 * @param args.model - The model to use for classification.
 * @param args.choices - The possible classification choices (defaults to DOCUMENT_RELEVANCY_CHOICES).
 * @param args.promptTemplate - The prompt template to use (defaults to DOCUMENT_RELEVANCY_TEMPLATE).
 * @param args.telemetry - The telemetry to use for the evaluator.
 *
 * @returns An evaluator function that takes a {@link DocumentRelevancyExample} and returns a classification result
 * indicating whether the document is relevant to the input question.
 *
 * @example
 * ```ts
 * const evaluator = createDocumentRelevancyEvaluator({ model: openai("gpt-4o-mini") });
 * const result = await evaluator({
 *   input: "What is the capital of France?",
 *   documentText: "Paris is the capital and most populous city of France.",
 * });
 * console.log(result.label); // "relevant" or "unrelated"
 * ```
 */
export function createDocumentRelevancyEvaluator(args) {
    const { choices = DOCUMENT_RELEVANCY_CHOICES, promptTemplate = DOCUMENT_RELEVANCY_TEMPLATE, ...rest } = args;
    const documentRelevancyEvaluatorFn = createClassifier({
        ...args,
        promptTemplate,
        choices,
        ...rest,
    });
    return documentRelevancyEvaluatorFn;
}
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