(Or Evils as I'm coming to think of them)

We want to build an open-source, sane way to score the performance of LLM calls that is:

• local first - so you don't need to use a service
• flexible enough to work with whatever best practice emerges — ideally usable for any code that is stochastic enough to require scoring beyond passed/failed (that means LLM SDKs directly or even other agent frameworks)
• usable both for "offline evals" (unit-test style checks on performance) and "online evals" measuring performance in production or equivalent (presumably using an observability platform like Pydantic Logfire)
• usable with Pydantic Logfire when and where that actually helps

I believe @dmontagu has a plan.