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evaluerBench

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The Need for Telemetry

When working with Local LLMs, understanding why an agent failed is just as important as knowing that it failed. I built evaluerBench to parse, visualize, and compare complex AI evaluation data in real time.

Architectural Choices

The dashboard focuses on high-density information display. By adopting an LCARS-inspired matrix grid and detailed side-by-side comparison views, I can quickly scan pass/fail rates, identify timeout regressions, and even launch fully interactive HTML/JS artifacts generated by the model directly within an iframe sandbox.

Tech Stack

  • Framework: Astro
  • Styling: Vanilla CSS (CSS Variables, Flexbox/Grid)
  • Data: JSON serialized telemetry blobs