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Comment on Show HN: A murder mystery game built on an open-source gen-AI agent frameworkparent

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I'm going to write out a short idea...

We need a prompt that is situational, that morphs with interaction.

So we have a prompt provided by python fstrings:

f""" # Actions context could be up here. You would ammend the "reply" section below with "reply with words or an action".

This is a summary of your recent interaction with PLAYER CHARACTER: { self.recent_memory() }

This is how you feel about PLAYER CHARACTER: { self.disposition() }

Your current conversation with PLAYER CHARACTER is: { self.conversation }

Score how the last reply effects you emotionally using this format <some extractable format with a function call>

Replying in a tone consistent with your disposition towards PLAYER CHARACTER, you say: """

self.recent_memory would be a summary of previous discussions and decreasing granularity the farther in time they are. Eventually the content of the memory fades, and only the emotional impact remains.

This could also be applied to general memories, where you would run a prompt through the situation you want the character to remember and then that gets embedded in the emotional/memory and recalled "realistically".

self.disposition would be a short text description of how the character feels about the player's character as well as a scoring mechanism that weights the effect of recent conversations against prior conversations.

Actions could be embedded into the prompt to allow the character to do stuff when so inclined.

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