@arizeai/phoenix-evals
Version:
A library for running evaluations for AI use cases
40 lines • 1.89 kB
TypeScript
import { CreateClassifierArgs, EvaluatorFn } from "../types/evals.js";
export interface DocumentRelevancyEvaluatorArgs extends Omit<CreateClassifierArgs, "promptTemplate" | "choices"> {
choices?: CreateClassifierArgs["choices"];
promptTemplate?: CreateClassifierArgs["promptTemplate"];
}
/**
* An example to be evaluated by the document relevancy evaluator.
*/
export type DocumentRelevancyExample = {
input: string;
documentText: string;
};
/**
* 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 declare function createDocumentRelevancyEvaluator(args: DocumentRelevancyEvaluatorArgs): EvaluatorFn<DocumentRelevancyExample>;
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