Great question, chainforge looks interesting!

We offer auto-evals as one tool in the toolbox. We also consider structured output validations, semantic similarity to an expected result, and manual feedback gathering. If anything, I've seen that people are more skeptical of LLM auto-eval because of the inherent circularity, rather than over-trusting it.

Do you have any suggestions for other evaluation methods we should add? We just got started in July and we're eager to incorporate feedback and keep building.