daoing/dsh-daoing-memory

README 摘要

dsh-daoing-memory Self-evolving memory for DeepSeek Harness (DSH) — earned experiences, diary/fact semantic memory, concern tracking, and an append-only audit ledger. 中文文档 → An agent without memory starts from zero every session. dsh-daoing-memory gives a DSH agent a persistent, self-improving memory that it earns through use: it keeps a diary, distills durable facts and open concerns about the user, accumulates verified experiences, recalls what is relevant, revises what turned out wrong, and records every change in an auditable ledger. The design follows four verbs — 生 · 用 · 修 · 记 ( Generate · Use · Revise · Record ). Why Most "memory" bolt-ons either dump raw conversation into a vector store, or let the model write anything it likes into a key-value blob. Both fail in practice: the first buries signal in noise, the second lets a single hallucination poison every future session. dsh-daoing-memory takes a different stance: - Memory must be earned. An experience starts as a low-trust candidate and is promoted only after it is corroborated by real use. Nothing reaches high trust by fiat. - Two distinct memories. Semantic memory (durable facts about the user + open concerns they care…

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