dsh-tdai-memory

In AI conversations, we often face the frustration of starting fresh each time—assistants forget past interactions, lack context continuity, and cannot recall personal preferences. The dsh-tdai-memory plugin tackles this by porting Tencent Cloud's open-source TencentDB Agent Memory system into DeepSeek Harness, enabling robust long-term memory. This means your chat history, extracted facts, preferences, and even user profiles are persistently stored and intelligently reused, allowing the model to 'remember' who you are and what you've discussed in every session.

At its core lies a four-layer architecture: L0 captures every raw conversation turn; L1 uses a background LLM to extract structured memories (facts, events, instructions); L2 and L3 generate scene blocks and persona profiles. Crucially, it features automatic recall injection—dynamically retrieving relevant memories and user profiles based on current messages during prompt assembly, seamlessly enriching context for personalized responses. The plugin also offers search tools for flexible querying of raw conversations and structured memories, making memory management efficient and intuitive.

dsh-tdai-memory is ideal for users needing long-term, deep interactions—content creators, researchers, or anyone wanting an AI assistant that adapts to their habits. Developers building intelligent, human-centric applications will also find it invaluable, as it provides a ready-made, sophisticated memory system to enhance models without starting from scratch. Whether for personal productivity or product development, this plugin marks a shift from stateless to 'memory-aware' AI interactions.