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A Generative AI Engineer is building an internal code assistant to help developers write and debug Python functions. During early testing, the LLM often hallucinates code, including non-existent libraries and APIs. The team wants to reduce such errors while preserving the assistant’s usefulness and creativity. Which approach should the engineer take to reduce hallucinations without overly restricting model behavior?