12.04.2025: Evaluator Message Formats

from phoenix.evals import ClassificationEvaluator, LLMevaluator = ClassificationEvaluator(    name="sentiment",    llm=LLM(provider="openai", model="gpt-4o-mini"),    prompt_template="Classify the sentiment: {text}",    choices=["positive", "negative", "neutral"])

import { createClassificationEvaluator } from "@arizeai/phoenix-evals";import { openai } from "@ai-sdk/openai";const evaluator = createClassificationEvaluator({  name: "sentiment",  model: openai("gpt-4o-mini"),  promptTemplate: "Classify the sentiment: {{text}}",  choices: { positive: 1, negative: 0, neutral: 0.5 },});

evaluator = ClassificationEvaluator(    name="helpfulness",    llm=llm,    prompt_template=[        {"role": "system", "content": "You evaluate response helpfulness."},        {"role": "user", "content": "Question: {question}\nAnswer: {answer}"}    ],    choices=["helpful", "somewhat_helpful", "not_helpful"])

const evaluator = createClassificationEvaluator({  name: "helpfulness",  model,  promptTemplate: [    { role: "system", content: "You evaluate response helpfulness." },    { role: "user", content: "Question: {{question}}\nAnswer: {{answer}}" },  ],  choices: { helpful: 1, somewhat_helpful: 0.5, not_helpful: 0 },});