Show HN: PromptTools – open-source tools for evaluating LLMs and vector DBs
I like the support for Vector DBs and LLaMa-2. I'm curious as to whether and what influences compelled PromptTools, and how it differs from other tools in this space. For context, we've also released a prompt engineering IDE, ChainForge, which is open-source and has many of the features here, such as querying multiple models at once, prompt templating, evaluating responses with Python/JS code and LLM scorers, plotting responses, etc (<a href="https://github.com/ianarawjo/ChainForge">https://github.com/ianarawjo/ChainForge</a> and a playground at <a href="http://chainforge.ai" rel="nofollow noreferrer">http://chainforge.ai</a>).<p>One big problem we're seeing in this space is over-trust in LLM scorers as 'evaluators'. I've personally seen that minor tweaks to a scoring prompt can sometimes result in vastly different evaluation 'results.' Given recent debacles (<a href="https://news.ycombinator.com/item?id=36370685">https://news.ycombinator.com/item?id=36370685</a>), I'm wondering how we can design LLMOps tools for evaluation which both support the use of LLMs as scorers, but also caution users about their results. Are you thinking similarly about this question, or seen usability testing which points to over-trust in 'auto-evaluators' as an emerging problem?