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dsh-plugin-semantic-memory

v0.2.1chenkezhen480 / dsh-semantic-memory0ab4575a7f

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Overview

dsh-plugin-semantic-memory

Semantic long-term memory for DeepSeek Harness: embedding-based retrieval over a persistent cross-session memory store, with model-facing tools, proactive per-question recall, automatic conversation summarization, and auto-selected embedding provider (apiKey present → API, otherwise local).

README / EN

Package documentation

Registry summary

Semantic long-term memory for DeepSeek Harness: embedding-based retrieval over a persistent cross-session memory store, with model-facing tools, proactive per-question recall, automatic conversation summarization, and auto-selected embedding provider (apiKey present → API, otherwise local).

dsh.pub verifies the pinned bundle contract, runtime facts, and distribution semantics. The complete README remains in the source repository.

Read the full README on GitHub

LIMITATIONS

Known limitations

- **Recall is best-effort and async** — the user-message listener embeds in the background; on a cold start (model still downloading) or with a slow API the first recall may arrive one step late, and the strength-ranked fallback covers that turn. Recall caches are per-session and stale after 60 s. - **Sync prompt injection** — the injected section renders from resident data only; the store is loaded lazily on first tool call, so a brand-new process may start with an empty injection for the first assembly. - **No embedding persistence cache** — vectors are stored inside each entry, so no separate index file is needed, but full re-embedding never happens either (entries keep their vectors forever). - **Brute-force search** — O(n) cosine over all entries per query; fine for personal-scale stores (thousands), not for millions of entries.