@arizeai/phoenix-evals/dist/esm/types/evals.d.ts

A library for running evaluations for AI use cases

import { LanguageModel } from "ai";
import { WithTelemetry } from "./otel.js";
/**
 * A specific AI example that is under evaluation
 */
export interface ExampleRecord<OutputType, InputType> {
    output: OutputType;
    expected?: OutputType;
    input?: InputType;
    [key: string]: unknown;
}
export interface WithLLM {
    model: LanguageModel;
}
export interface LLMEvaluationArgs extends WithLLM {
}
/**
 * The result of an evaluation
 */
export interface EvaluationResult {
    /**
     * The score of the evaluation.
     * @example 0.95
     */
    score?: number;
    /**
     * The label of the evaluation.
     * @example "correct"
     */
    label?: string;
    /**
     * The explanation of the evaluation.
     * @example "The model correctly identified the sentiment of the text."
     */
    explanation?: string;
}
/**
 * The result of a classification
 */
export interface ClassificationResult {
    label: string;
    explanation?: string;
}
/**
 * The choice (e.g. the label and score mapping) of a classification based evaluation
 */
export interface ClassificationChoice {
    label: string;
    score: number;
}
/**
 * A mapping of labels to scores
 */
export type ClassificationChoicesMap = Record<string, number>;
/**
 * The arguments for creating a classification-based evaluator
 */
export interface CreateClassifierArgs extends WithTelemetry {
    model: LanguageModel;
    /**
     * The choices to classify the example into.
     * e.g. { "correct": 1, "incorrect": 0 }
     */
    choices: ClassificationChoicesMap;
    /**
     * The prompt template to use for classification
     */
    promptTemplate: string;
}
export type EvaluatorFn<ExampleType extends Record<string, unknown>> = (args: ExampleType) => Promise<EvaluationResult>;
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