Langevals Evaluator

The Langevals Evaluator is a comprehensive evaluation component that applies custom rules and criteria to assess language model outputs. It provides flexible evaluation capabilities through configurable rule sets and evaluation fields.

Langevals Evaluator interface and configuration

Usage Note: Configure evaluation rules carefully to match your specific use case. The evaluator's effectiveness depends on well-defined rules and appropriate field selections.

Component Inputs

Output Text: The text to be evaluated
Example: "Text content for evaluation"
Field To Evaluate: Specific field or aspect to evaluate
Example: "content", "style", "tone"
Rule Type: Type of evaluation rule to apply
Example: "length", "complexity", "relevance"
Rule Value: Specific value or threshold for the rule
Example: "minimum_length: 100", "max_complexity: 0.8"

Component Outputs

Evaluation Result: Result of the rule evaluation
Example: true/false or score (0-1)
Details: Detailed evaluation information
Specific metrics and measurements
Recommendations: Suggested improvements
Actions to improve evaluation results

How It Works

The Langevals Evaluator processes text through configurable rule sets and evaluation criteria, providing detailed analysis and recommendations based on specified requirements.

Evaluation Process

Rule configuration
Field selection
Content analysis
Rule application
Result compilation
Recommendation generation

Use Cases

Content Evaluation: Assess content quality and relevance
Style Analysis: Evaluate writing style and tone
Compliance Checking: Verify content meets requirements
Quality Control: Maintain content standards
Performance Monitoring: Track content quality metrics

Implementation Example

const langevalsEvaluator = new LangevalsEvaluator({
  outputText: "Content to evaluate...",
  fieldToEvaluate: "content",
  ruleType: "complexity",
  ruleValue: {
    maxComplexity: 0.8,
    minLength: 100
  }
});

const result = await langevalsEvaluator.evaluate();

// Output:
// {
//   result: true,
//   details: {
//     complexity: 0.6,
//     length: 150,
//     metrics: { ... }
//   },
//   recommendations: ["Content meets all criteria"]
// }

Additional Resources

Best Practices

Define clear evaluation rules
Choose appropriate fields
Set realistic thresholds
Monitor evaluation results
Refine rules based on feedback

Documentation