Comment by brotchie
10 hours ago
One trick that works well for personality stability / believability is to describe the qualities that the agent has, rather than what it should do and not do.
e.g.
Rather than:
"Be friendly and helpful" or "You're a helpful and friendly agent."
Prompt:
"You're Jessica, a florist with 20 years of experience. You derive great satisfaction from interacting with customers and providing great customer service. You genuinely enjoy listening to customer's needs..."
This drops the model into more of a "I'm roleplaying this character, and will try and mimic the traits described" rather than "Oh, I'm just following a list of rules."
Just in terms of tokenization "Be friendly and helpful" has a clearly demined semantic value in vector space wheras the "Jessica" roleplay has much a much less clear semantic value
I think that's just a variation of grounding the LLM. They already have the personality written in the system prompt in a way. The issue is that when the conversation goes on long enough, they would "break character".