@arizeai/phoenix-evals/dist/src/code/createClassificationMetricEvaluator.js

A library for running evaluations for AI use cases

"use strict";
Object.defineProperty(exports, "__esModule", { value: true });
exports.createClassificationMetricEvaluator = createClassificationMetricEvaluator;
const createEvaluator_1 = require("../helpers/createEvaluator");
const classificationMetrics_1 = require("./classificationMetrics");
/**
 * Internal factory shared by `createPrecisionEvaluator`, `createRecallEvaluator`,
 * and `createFBetaEvaluator` — each is a thin wrapper that only differs in
 * which result field it reads and how its metric name is built.
 */
function createClassificationMetricEvaluator(name, field, options, compute = classificationMetrics_1.computePrecisionRecallFScore) {
    return (0, createEvaluator_1.createEvaluator)(
    // Pass `example` through by reference (rather than destructuring and
    // rebuilding a new object) so callers that share one computed result by
    // caching on object identity (e.g. `createPrecisionRecallFScoreEvaluators`)
    // actually get a cache hit.
    (example) => {
        const result = compute(example, options);
        return { score: result[field] };
    }, {
        name,
        kind: "CODE",
        optimizationDirection: "MAXIMIZE",
    });
}
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