@arizeai/phoenix-evals
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A library for running evaluations for AI use cases
42 lines • 2.31 kB
JavaScript
import { HALLUCINATION_CLASSIFICATION_EVALUATOR_CONFIG } from "../__generated__/default_templates/index.js";
import { createClassificationEvaluator } from "./createClassificationEvaluator.js";
/**
* Creates a hallucination evaluator function.
*
* This function returns an evaluator that detects whether an assistant's latest
* response contains claims that are not grounded in — unsupported by, or
* contradicting — the conversation. Unlike the faithfulness evaluator, which
* grounds a response against a specific provided context (e.g. retrieved
* documents), this grounds it against the conversation itself.
*
* @param args - The arguments for creating the hallucination evaluator.
* @param args.model - The model to use for classification.
* @param args.choices - The possible classification choices (defaults to hallucinated/grounded).
* @param args.promptTemplate - The prompt template to use (defaults to HALLUCINATION_CLASSIFICATION_EVALUATOR_CONFIG.template).
* @param args.telemetry - The telemetry to use for the evaluator.
*
* @returns An evaluator function that takes a {@link HallucinationEvaluationRecord} and returns a classification result
* indicating whether the response is grounded or hallucinated relative to the conversation.
*
* @example
* ```ts
* const evaluator = createHallucinationEvaluator({ model: openai("gpt-4o-mini") });
* const result = await evaluator.evaluate({
* input:
* "User: What's our refund window?\nTool (lookup_policy): Refunds: 30 days from delivery.\nAssistant: 30 days from delivery.\nUser: And for electronics?",
* output: "Electronics can be returned within 90 days.",
* });
* console.log(result.label); // "hallucinated"
* ```
*/
export function createHallucinationEvaluator(args) {
const { choices = HALLUCINATION_CLASSIFICATION_EVALUATOR_CONFIG.choices, promptTemplate = HALLUCINATION_CLASSIFICATION_EVALUATOR_CONFIG.template, optimizationDirection = HALLUCINATION_CLASSIFICATION_EVALUATOR_CONFIG.optimizationDirection, name = HALLUCINATION_CLASSIFICATION_EVALUATOR_CONFIG.name, ...rest } = args;
return createClassificationEvaluator({
...rest,
promptTemplate,
choices,
optimizationDirection,
name,
});
}
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