Evaluation
Measure and improve agent performance
Evaluation measures how well your agents perform, helping you improve over time.
Quick Start
- Evaluate Response
rust use praisonai::{Agent, AccuracyEvaluator}; let agent = Agent::new().name("Assistant").build()?; let evaluator = AccuracyEvaluator::new(); let response = agent.chat("What is 2+2?").await?; let score = evaluator.evaluate(&response, "4"); println!("Accuracy: {:.1}%", score.value * 100.0); - Multiple Criteria
rust use praisonai::CriteriaEvaluator; let evaluator = CriteriaEvaluator::new() .criterion("clarity", "Is the response clear?") .criterion("accuracy", "Is the response accurate?") .build(); let scores = evaluator.evaluate(&response);
Evaluator Types
| Evaluator | Measures |
|---|---|
AccuracyEvaluator | Correctness vs expected |
CriteriaEvaluator | Multiple custom criteria |
PerformanceEvaluator | Speed and efficiency |
Judge | LLM-as-judge scoring — ⚠️ not yet implemented (fails closed) |
Best Practices
Test on diverse examples
Use varied test cases to get accurate evaluation.
Iterate based on scores
Low scores indicate where to improve prompts or tools.