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Models that use sliding window attention can only resume a sequence from the cache if it falls within the saved windows. This works well if the next message picks up where the old one left off. However, it generally prevents a partial prefix match unless the entire conversation falls within the sliding window. This can be a problem with reasoning models where the traces are supposed to be removed from future messages, forcing the entire history to be re-evaluated. This change allows models to specify that a larger amount of the history be retained in memory, to allow more partial resumption. It still respects the window that the model was trained on for token generation.