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I don't understand what this is. 😅 it looks like it's just mapping your input/expected over a function? why do you need a custom test runner for this? and how is it local first? most useful models are too large to run locally. some sort of API response cache/recorder is probably what I need? 🤔

1. First, evals return a score, not a pass/fail metric. So you need a custom test runner to see the scores. 2. Good evals also need a UI attached so you can view the results, since you often need to verify the LLM app's output with human eyes.

1. It's not enough to know whether you are above a certain arbitrary number. You need to be able to dive into the data and view all outputs. You also need to see historical changes over time.

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