LLM Prompt Eval Tool was built to help developers analyze, compare, and refine AI prompts across multiple large language models — all within a consistent and measurable framework.
Instead of manually testing and guessing which prompt performs better, this tool lets you run evaluations automatically, gather metrics, and visualize which model delivers the most accurate or context-relevant output.
Each test includes side-by-side comparisons, success rate tracking, and scoring logic that allows teams to iterate quickly and improve their prompt performance over time.
The evaluation process follows a transparent structure — every step from input to output can be monitored, logged, and optimized.
It’s an essential internal utility at Pythagora, but it’s also fully open-source — designed so any developer can integrate it into their workflow, whether for AI app development, research, or model fine-tuning.
