IsEmailScorer
Validates whether the prediction contains a valid email address format. Uses regular expression matching to check for properly formatted email addresses in standalone strings or text.
Overview
Validates whether the prediction contains a valid email address format. Uses regular expression matching to check for properly formatted email addresses in standalone strings or text.
Use Cases
- Structured output validation
How It Works
This scorer uses deterministic rule-based evaluation to validate outputs against specific criteria. It applies predefined rules and patterns to assess the response, providing consistent and reproducible results without requiring LLM inference.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
| prediction | str | Yes | Text to validate for email format |
Output Schema
| Field | Type | Description |
|---|---|---|
| score | float | 10.0 if valid email, partial for format-only valid |
| passed | bool | True if valid email found |
| reasoning | str | Validation details |
| metadata.email_valid | bool | Whether email is valid |
| metadata.format_valid | bool | Whether format is valid |
Score Interpretation
Default threshold: 10/10
Related Scorers
Frequently Asked Questions
When should I use this scorer?
Use IsEmailScorer when you need to evaluate format and rule-based aspects of your AI outputs. It's particularly useful for structured output validation.
Why doesn't this scorer need expected output?
This scorer evaluates quality aspects that don't require comparison against a reference answer. It uses the system prompt and context as the implicit ground truth.
Can I customize the threshold?
Yes, the default threshold of 10 can be customized when configuring the scorer.
Quick Info
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