05.14.2025: Experiments in the JS client

Experiments In The JS Client#

You can now run Experiments using the Phoenix JS client! Use Experiments to test different iterations of your applications over a set of test cases, then evaluate the results.

This release includes:

Native tracing of tasks and evaluators
Async concurrency queues
Support for any evaluator (including bring your own evals)

Code Implementation#

import { createClient } from "@arizeai/phoenix-client";import {  asEvaluator,  runExperiment,} from "@arizeai/phoenix-client/experiments";import type { Example } from "@arizeai/phoenix-client/types/datasets";import { Factuality } from "autoevals";import OpenAI from "openai";const phoenix = createClient();const openai = new OpenAI();/** Your AI Task */const task = async (example: Example) => {  const response = await openai.chat.completions.create({    model: "gpt-4o",    messages: [      { role: "system", content: "You are a helpful assistant." },      { role: "user", content: JSON.stringify(example.input, null, 2) },    ],  });  return response.choices[0]?.message?.content ?? "No response";};await runExperiment({  dataset: "dataset_id",  experimentName: "experiment_name",  client: phoenix,  task,  evaluators: [    asEvaluator({      name: "Factuality",      kind: "LLM",      evaluate: async (params) => {        const result = await Factuality({          output: JSON.stringify(params.output, null, 2),          input: JSON.stringify(params.input, null, 2),          expected: JSON.stringify(params.expected, null, 2),        });        return {          score: result.score,          label: result.name,          explanation: (result.metadata?.rationale as string) ?? "",          metadata: result.metadata ?? {},        };      },    }),  ],});