DreamTalk's Four-Layer Memory Engine Keeps AI Companions Coherent Beyond 30 Turns

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AI companion apps commonly suffer from two problems: context amnesia after 20–30 conversation turns due to sliding-window limits, and persona drift where characters revert to generic assistant behavior. A DEV Community article details the architecture behind DreamTalk (dreamtalk.cc.cd), an immersive virtual companion product designed to address both issues. The system uses a four-layer temporal memory engine comprising working memory, episodic memory, a semantic relationship graph, and a nightly reflection-and-consolidation layer. Important user events are scored, embedded with emotional valence, and stored in a vector database, while a graph layer tracks relationship-specific facts such as shared promises or personal dislikes. A dual anti-drift mechanism combining hard persona constraints injected into prompts and post-hoc style-correction tokens is credited with maintaining character consistency over several months of interaction.

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