Answer: Decrease the temperature to 0.2

**Explanation:** Temperature is a parameter that controls the randomness of LLM responses: - **Lower temperature (e.g., 0.2)**: Makes outputs more deterministic and focused on the highest probability tokens, reducing randomness while still allowing slight variability - **Higher temperature (e.g., 1.2)**: Increases randomness and creativity, making outputs more diverse but less consistent **Why B is correct:** - Decreasing temperature to 0.2 reduces randomness while maintaining slight variability - This makes responses more stable and deterministic, addressing the team's concern about inconsistent outputs **Why other options are incorrect:** - **A (Increase temperature to 1.2)**: Would make responses even more random and inconsistent - **C (Increase top-k to 200)**: Top-k sampling limits choices to k most likely tokens; increasing it allows more options but doesn't directly address randomness control - **D (Increase top-p to 0.95)**: Top-p (nucleus sampling) selects from tokens whose cumulative probability exceeds p; increasing it includes more tokens but doesn't specifically increase determinism **Key Concept:** Temperature is the primary parameter for controlling randomness vs. determinism in LLM outputs.

Author: Ritesh Yadav