LLM call batching and multithreading#266
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This PR includes #265 (which includes #264).
It adds performance/cost improvements by supporting batching: when we evaluate N results from a query, we break that N into micro-batches (of configurable size) and send them to the LLM at once. You'd typically need a clearer prompt and possibly even a better model, but in my experience, it pays off. Because a good prompt might get quite big.
Side-effect: the prompt is now configurable (for the batch case at least).
We can also parallelize both generating queries from docs and generating judgments from query-doc pairs.
Both features are opt-in. Previous behavior is pretty much as it used to be.