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ExamplesEvalsContent Similarity

Content Similarity

This example demonstrates how to use Mastra’s Content Similarity metric to evaluate the textual similarity between two pieces of content.

Overview

The example shows how to:

  1. Configure the Content Similarity metric
  2. Compare different text variations
  3. Analyze similarity scores
  4. Handle different similarity scenarios

Setup

Dependencies

Import the necessary dependencies:

src/index.ts
import { ContentSimilarityMetric } from '@mastra/evals/nlp';

Metric Configuration

Set up the Content Similarity metric:

src/index.ts
const metric = new ContentSimilarityMetric();

Example Usage

High Similarity Example

Compare nearly identical texts:

src/index.ts
const text1 = 'The quick brown fox jumps over the lazy dog.';
const reference1 = 'A quick brown fox jumped over a lazy dog.';
 
console.log('Example 1 - High Similarity:');
console.log('Text:', text1);
console.log('Reference:', reference1);
 
const result1 = await metric.measure(reference1, text1);
console.log('Metric Result:', {
  score: result1.score,
  info: {
    similarity: result1.info.similarity,
  },
});
// Example Output:
// Metric Result: { score: 0.7761194029850746, info: { similarity: 0.7761194029850746 } }

Moderate Similarity Example

Compare texts with similar meaning but different wording:

src/index.ts
const text2 = 'A brown fox quickly leaps across a sleeping dog.';
const reference2 = 'The quick brown fox jumps over the lazy dog.';
 
console.log('Example 2 - Moderate Similarity:');
console.log('Text:', text2);
console.log('Reference:', reference2);
 
const result2 = await metric.measure(reference2, text2);
console.log('Metric Result:', {
  score: result2.score,
  info: {
    similarity: result2.info.similarity,
  },
});
// Example Output:
// Metric Result: {
//   score: 0.40540540540540543,
//   info: { similarity: 0.40540540540540543 }
// }

Low Similarity Example

Compare distinctly different texts:

src/index.ts
const text3 = 'The cat sleeps on the windowsill.';
const reference3 = 'The quick brown fox jumps over the lazy dog.';
 
console.log('Example 3 - Low Similarity:');
console.log('Text:', text3);
console.log('Reference:', reference3);
 
const result3 = await metric.measure(reference3, text3);
console.log('Metric Result:', {
  score: result3.score,
  info: {
    similarity: result3.info.similarity,
  },
});
// Example Output:
// Metric Result: {
//   score: 0.25806451612903225,
//   info: { similarity: 0.25806451612903225 }
// }

Understanding the Results

The metric provides:

  1. A similarity score between 0 and 1:
    • 1.0: Perfect match - texts are identical
    • 0.7-0.9: High similarity - minor variations in wording
    • 0.4-0.6: Moderate similarity - same topic with different phrasing
    • 0.1-0.3: Low similarity - some shared words but different meaning
    • 0.0: No similarity - completely different texts




View Example on GitHub
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