July 22, 2025

Enhancements in `llm-benchmark`: Improved CLI and Debug Logging

The llm-benchmark project is a powerful tool designed to optimize and benchmark code using Large Language Models (LLMs) across multiple providers. It ensures that the optimized code variants are functionally equivalent to the original before benchmarking them for performance metrics like operations per second, memory usage, and cost analysis. This post will cover the recent updates to the project, focusing on improvements to the CLI and debug logging.

Recent Updates

Improved CLI Help and Debug Logging

The latest updates to llm-benchmark include enhancements to the command-line interface (CLI) and debug logging capabilities. These improvements aim to make the tool more user-friendly and provide better insights during the test case discovery process.

Key Changes

CLI Help Display: The CLI now automatically displays help information when run without any arguments. This change helps users quickly understand the available commands and options without needing to refer to external documentation.
Verbose Debug Logging: A new verbose debug logging feature has been added to assist in test case discovery. This feature provides detailed logs of the paths and patterns being checked, which is invaluable for diagnosing issues related to test file discovery.
Error Message Improvements: Error messages related to missing test files have been improved to provide clearer guidance on resolving such issues.
Debug Logging Flag: The debug logging is now controlled by a --debug flag, ensuring that verbose logs are only shown when explicitly requested. This change helps keep the output clean during normal operation.

Code Changes

The following code snippets highlight the key changes made to implement these features:

CLI Help Display:

// Show help when CLI is run without arguments
    if (!args.length) {
      console.log(cliHelpMessage);
      process.exit(0);
    }

Debug Logging Implementation:

// Debug logs now only show when --debug flag is enabled
    const validationRunner = new ValidationRunner(config, plugin, options.debug);

Test Case Loader Update:

// Updated TestCaseLoader to respect debug flag
    testCaseLoader = new TestCaseLoader(config, options.debug);

Installation and Usage

To get started with llm-benchmark, you can install it globally via npm:

npm install -g llm-benchmark

Or use it directly with npx:

npx llm-benchmark demo

Running Benchmarks

To run a benchmark, use the following command:

llm-benchmark optimize yourFunction.js --providers openai:gpt-4o --debug

The --debug flag will enable verbose logging, providing detailed insights into the test case discovery process.

Technical Architecture

The llm-benchmark tool is built using TypeScript and is designed to be modular and extensible. It supports multiple programming languages and LLM providers, making it a versatile tool for developers looking to optimize their code with AI.

Future Roadmap

Future updates may include additional provider support, enhanced benchmarking metrics, and further improvements to the CLI and logging features. The project is open-source, and contributions are welcome.

Links and Resources

These updates make llm-benchmark more robust and user-friendly, providing developers with the tools they need to optimize and benchmark their code effectively.

Enhancements in llm-benchmark: Improved CLI and Debug Logging