Validating the structure and patterns of text is critical for ensuring the reliability, usability, and accuracy of generated content. Whether it’s checking if a response meets specific length requirements, follows formatting rules, or adheres to regex patterns, these validations play an essential role in maintaining quality control.Need for validating text structure in AI-generated content can help detect issues in responses that are too short, too long, or nonsensical, missing required phrases or keywords or has deviations from expected formats, such as URLs, email addresses, or numerical data. By incorporating below evaluations, developers can ensure that AI systems generate text that is logical, meaningful, and aligned with task-specific requirements.Below are the evals provided by Future AGI that validates text based on structure, length, and patterns:
Checks if the text matches a specified regex pattern. This evaluation is particularly useful for checking structured data formats such as phone numbers, email addresses, dates, or custom-defined patterns.Click here to read the eval definition of Regex