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Claudio Santini’s primer on Unvibe reveals a Python library that treats unit-tests as a reward function, guiding LLM-driven Monte Carlo Tree Search to generate code that passes all tests. It details how Unvibe decorates functions with @ai, uses unvibe.TestCase for granular scoring, and iteratively refines implementations by feeding back assertion errors to the model.

https://claudio.uk/posts/unvibe-a-python-test-runner-that-generates-correct-implementations.html
claudio.uk A Python Test-Runner that generates correct implementations Unvibe: A Python Test-Runner that generates correct code
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