Code Generation

Evaluate LLMs on generating executable code. Spot syntax or logic errors and improve development workflows.

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The Code Generation Metrics suite in RagaAI Catalyst evaluates the accuracy, robustness, and functionality of code generated by LLMs. These metrics assess aspects like structural correctness, similarity to reference code, adaptability to prompt changes, and success in passing functional tests. By measuring code-specific factors such as n-gram overlap, logical consistency, and robustness across prompt variations, these metrics provide comprehensive insights into the reliability and precision of code generation models.

Functional CorrectnessChrFRubyCodeBLEURobust Pass@kRobust Drop@kPass-Ratio@n