@arizeai/phoenix-evals/dist/src/llm/createClassifier.js

A library for running evaluations for AI use cases

"use strict";
var __rest = (this && this.__rest) || function (s, e) {
    var t = {};
    for (var p in s) if (Object.prototype.hasOwnProperty.call(s, p) && e.indexOf(p) < 0)
        t[p] = s[p];
    if (s != null && typeof Object.getOwnPropertySymbols === "function")
        for (var i = 0, p = Object.getOwnPropertySymbols(s); i < p.length; i++) {
            if (e.indexOf(p[i]) < 0 && Object.prototype.propertyIsEnumerable.call(s, p[i]))
                t[p[i]] = s[p[i]];
        }
    return t;
};
Object.defineProperty(exports, "__esModule", { value: true });
exports.createClassifier = createClassifier;
const generateClassification_1 = require("./generateClassification");
const template_1 = require("../template");
/**
 * Convert a mapping of choices to labels
 * Asserts that the choices are valid
 */
function choicesToLabels(choices) {
    const labels = Object.keys(choices);
    if (labels.length < 1) {
        throw new Error("No choices provided");
    }
    return labels;
}
/**
 * A function that serves as a factory that will output a classification evaluator
 */
function createClassifier(args) {
    const { model, choices, promptTemplate } = args, rest = __rest(args, ["model", "choices", "promptTemplate"]);
    return async (args) => {
        const templateVariables = Object.assign({}, args);
        const prompt = (0, template_1.formatTemplate)({
            template: promptTemplate,
            variables: templateVariables,
        });
        const classification = await (0, generateClassification_1.generateClassification)(Object.assign({ model, labels: choicesToLabels(choices), prompt }, rest));
        // Post-process the classification result and map it to the choices
        const score = choices[classification.label];
        return Object.assign({ score }, classification);
    };
}
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