Promptim is an experimental library aimed at improving AI system prompts through automated optimization. By utilizing datasets, custom evaluators, and optional human feedback, Promptim refines prompts to enhance performance. It involves an iterative process where new prompts are generated, evaluated, and retained if they show improvements. Integrating with LangSmith, it offers robust dataset management and evaluation capabilities. While it can expedite prompt engineering and bring rigor to the process, human oversight remains essential for final results.
Table of contents
From evaluation-driven development to prompt optimizationWhy do prompt optimization?How Promptim worksLimitations of prompt optimizationComparing Promptim to DSPyFuture workSort: