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dsh-memory-evolve

brianwang2007xjtu/dsh-memory-evolve

Empowers DeepSeek Harness AI with cross-session long-term memory, manages your to-dos and skills, and orchestrates multiple AI sessions and external agents to collaborate—it learns from you over time, so context stays intact even when you switch conversations.

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安装参考

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dsh plugin --profile web add github:brianwang2007xjtu/dsh-memory-evolve

该命令指向仓库当前默认分支;尚无绑定当前 commit 的完整验证结果。

PROJECT README

README

dsh-memory-evolve

Evolving long-term memory for the DeepSeek Harness: durable, decay-reinforced memories persisted through the storage-domain form (JSON backend under $DSH_HOME/storages).

Tools

  • memory_remember — add/update a memory; near-duplicate content merges into the existing entry instead of creating a duplicate.
  • memory_recall — retrieve memories by query/tags, ranked by relevance + importance + recency; reading a memory reinforces it.
  • memory_evolve — force one consolidation pass: decay importance by age, merge near-duplicates, prune below the retention threshold.
  • memory_forget — delete one memory by id, or clear the whole workspace.

Memories are namespaced by the session's workspace (cwd), falling back to namespace for sessions without a workspace.

Configuration

- id: memory-evolve
  name: dsh-memory-evolve
  config:
    namespace: global      # fallback namespace
    maxMemories: 1000      # per-namespace cap (oldest pruned first)
    decayHalfLifeDays: 30  # effectiveImportance = importance * 0.5^(age/halfLife)
    pruneBelow: 0.05       # prune memories whose effective importance drops below this
    mergeThreshold: 0.8    # Jaccard similarity above which memories merge
    recallLimit: 10        # default recall limit

Installation

dsh plugin --profile web add link:/path/to/dsh-memory-evolve

Then mount it with the patch row above in the profile's cordis.patch.yml.

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