A conversational assistant routes requests to Anthropic Claude through Amazon Bedrock. Users notice that asking similar questions multiple times sometimes yields different answers. To make responses more consistent and less random, what parameter changes should the ML engineer apply?

To make responses more consistent and less random, an ML engineer should decrease both the temperature and topk parameters. Temperature controls the randomness of the output: a lower temperature (closer to 0) makes the model more deterministic and less creative, leading to more consistent answers. Topk limits the number of highest-probability tokens considered for the next word. Decreasing topk restricts the model to a smaller, more probable set of options, further reducing variability. Increasing these parameters would have the opposite effect, making responses more diverse and less consistent.