@arizeai/phoenix-evals
Version:
A library for running evaluations for AI use cases
71 lines (67 loc) • 2.85 kB
text/typescript
import { CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG } from "../__generated__/default_templates";
import type { CreateClassificationEvaluatorArgs } from "../types/evals";
import type { ClassificationEvaluator } from "./ClassificationEvaluator";
import { createClassificationEvaluator } from "./createClassificationEvaluator";
export interface CorrectnessEvaluatorArgs<
RecordType extends Record<string, unknown> = CorrectnessEvaluationRecord,
> extends Omit<
CreateClassificationEvaluatorArgs<RecordType>,
"promptTemplate" | "choices" | "optimizationDirection" | "name"
> {
optimizationDirection?: CreateClassificationEvaluatorArgs<RecordType>["optimizationDirection"];
name?: CreateClassificationEvaluatorArgs<RecordType>["name"];
choices?: CreateClassificationEvaluatorArgs<RecordType>["choices"];
promptTemplate?: CreateClassificationEvaluatorArgs<RecordType>["promptTemplate"];
}
/**
* A record to be evaluated by the correctness evaluator.
*/
export type CorrectnessEvaluationRecord = {
input: string;
output: string;
};
/**
* Creates a correctness evaluator function.
*
* This function returns an evaluator that determines whether a given output
* is factually accurate, complete, logically consistent, and uses precise terminology.
*
* @param args - The arguments for creating the correctness evaluator.
* @param args.model - The model to use for classification.
* @param args.choices - The possible classification choices (defaults to CORRECTNESS_CHOICES).
* @param args.promptTemplate - The prompt template to use (defaults to CORRECTNESS_TEMPLATE).
* @param args.telemetry - The telemetry to use for the evaluator.
*
* @returns An evaluator function that takes a {@link CorrectnessEvaluationRecord} and returns a classification result
* indicating whether the output is correct or incorrect.
*
* @example
* ```ts
* const evaluator = createCorrectnessEvaluator({ model: openai("gpt-4o-mini") });
* const result = await evaluator.evaluate({
* input: "What is the capital of France?",
* output: "Paris is the capital of France.",
* });
* console.log(result.label); // "correct" or "incorrect"
* ```
*/
export function createCorrectnessEvaluator<
RecordType extends Record<string, unknown> = CorrectnessEvaluationRecord,
>(
args: CorrectnessEvaluatorArgs<RecordType>
): ClassificationEvaluator<RecordType> {
const {
choices = CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG.choices,
promptTemplate = CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG.template,
optimizationDirection = CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG.optimizationDirection,
name = CORRECTNESS_CLASSIFICATION_EVALUATOR_CONFIG.name,
...rest
} = args;
return createClassificationEvaluator<RecordType>({
...rest,
promptTemplate,
choices,
optimizationDirection,
name,
});
}