madage/dsh-self-improved

README excerpt

dsh-self-improved Long-term memory & self-evolving plugin for DeepSeek Harness (fully local). Status: M0–M6 complete and deployed to a real environment (web profile). Design/research docs stay local only (see .gitignore ). What it is Adds the two missing capabilities to DSH — "cross-session memory + self-evolution": - Memory : automatically distills key points from conversations (facts / preferences / events / instructions) into a local memory store; before each new turn, relevant memories are injected to the model — the AI "remembers you". - Self-evolution : memories are consolidated, decayed and corrected; successful workflows can be distilled into reusable skills; the user persona keeps evolving with conversations. The architecture follows the four-layer memory pyramid of TencentDB Agent Memory (L0 capture → L1 extraction → L2 scene grouping → L3 persona), but reuses DSH-native services ( ctx.llm / session events / agent/pre-step injection / dsh-skill / storageDomain ) with a fully local SQLite store (FTS5 + sqlite-vec). No data is uploaded anywhere. Roadmap Milestone Scope Status M0 Probe: event capture / recall injection / tool registration / settings namespace ✅ Verified (iso…

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