Memory DB

Liquina's Memory DB is a core component responsible for maintaining conversational continuity across both private and group interactions. Unlike simple logging mechanisms, Memory DB selectively structures and organizes past exchanges into retrievable memory units.

• Memory DB actively tracks key entities, user preferences, frequently mentioned topics, and conversational patterns to enrich future interactions.

• It supports both short-term and long-term memory, enabling Liquina to balance between remembering important details and avoiding overload from trivial data.

• Memories are organized and indexed internally to allow for low-latency retrieval even under frequent or parallel conversations.

• The system automatically filters and prioritizes information, focusing on recurring or contextually significant details.

• Liquina leverages Memory DB to reference past user interactions naturally, enabling her to recall prior topics, shared jokes, or group-specific dynamics.

• Outdated, obsolete, or irrelevant data is periodically pruned to maintain an efficient and focused memory space.

• Memory DB is integrated seamlessly with Liquina's conversational pipeline, providing context without interrupting response time.

• By combining entity recognition, dialogue state tracking, and lightweight summarization techniques, Memory DB helps Liquina maintain a sense of history.

• Memory data remains locally scoped to Liquina’s runtime environment and is designed with scalability in mind for future expansions.

• The specific implementation details, including storage structures and retrieval algorithms, are proprietary but optimized for consistent and reliable performance.