Jev in 25 Lines of Python | Hacker News
I've found that using structured outputs solves this problem much better. Instead of letting a model generate only "A", "B" or "C" and looking at the probs, have it directly generate "Legitimate", "Spam" or "Phishing" or any other pre-defined option from a set of multi-token sequences. Behind the scenes it boils down to something quite similar, but you're not running into the risk that the model actually wanted to say "A phishing attempt seems likely, so answer (C) is correct.", which would lead "A" to have the highest probability in the first token. You can even use a reasoning budget this way either via inherent reasoning or a free-form part preceding the remaining output structure. You can also have it assign probabilities (either in words or numbers) using more complex output structures, but I would not rely on them much more than the token logprobs (they can still be quite good though). reply I got this technique to work extremely reliably last year. However there were a bunch of