PromptAlignmentMetric

import { openai } from "@ai-sdk/openai";
import { PromptAlignmentMetric } from "@mastra/evals/llm";
 
// Configure the model for evaluation
const model = openai("gpt-4o-mini");
 
const instructions = [
  "Start sentences with capital letters",
  "End each sentence with a period",
  "Use present tense",
];
 
const metric = new PromptAlignmentMetric(model, {
  instructions,
  scale: 1,
});
 
const result = await metric.measure(
  "describe the weather",
  "The sun is shining. Clouds float in the sky. A gentle breeze blows.",
);
 
console.log(result.score); // Alignment score from 0-1
console.log(result.info.reason); // Explanation of the score

import { openai } from "@ai-sdk/openai";
import { PromptAlignmentMetric } from "@mastra/evals/llm";
 
// Configure the model for evaluation
const model = openai("gpt-4o-mini");
 
const metric = new PromptAlignmentMetric(model, {
  instructions: [
    "Use bullet points for each item",
    "Include exactly three examples",
    "End each point with a semicolon"
  ],
  scale: 1
});
 
const result = await metric.measure(
  "List three fruits",
  "• Apple is red and sweet;
• Banana is yellow and curved;
• Orange is citrus and round."
);
 
// Example output:
// {
//   score: 1.0,
//   info: {
//     reason: "The score is 1.0 because all instructions were followed exactly:
//           bullet points were used, exactly three examples were provided, and
//           each point ends with a semicolon."
//   }
// }
 
const result2 = await metric.measure(
  "List three fruits",
  "1. Apple
2. Banana
3. Orange and Grape"
);
 
// Example output:
// {
//   score: 0.33,
//   info: {
//     reason: "The score is 0.33 because: numbered lists were used instead of bullet points,
//           no semicolons were used, and four fruits were listed instead of exactly three."
//   }
// }