NattoCB/dsh-plugin-memory ↗★ 4

@deepseek-ai/dsh-plugin-memory

Persistent 5-layer memory system for DeepSeek Harness (entry injection, relevance retrieval, agent tools, and LLM-backed auto-extraction). 适合需要AI跨会话长期记住个人偏好和项目背景信息的用户。

패키지
@deepseek-ai/dsh-plugin-memory
호환성
미검증
Harness peer 범위
^0.1.0-rc.6
Cordis peer 범위
^4.0.1
버전
0.1.0-rc.1
라이선스
MIT
최근 업데이트
2026. 8. 21.

설치

$npx -p @deepseek-ai/dsh dsh plugin --profile web add github:NattoCB/dsh-plugin-memory

Configuration

Deploy the plugin via a DSH bundle entry (see cordis.patch.yml and package.json exports):

KeyDefaultMeaning
enableEntryInjectiontruePrepend the how-to-save + index block once per session.
enableRelevancetrueAppend relevant topic files per step (data-role=memory).
enableExtractiontrueIdle-time LLM auto-extraction.
maxRelevant5Max files surfaced per step (1–20).
relevanceTopK8Max candidates the LLM selector may pick from (1–40).
relevanceBudgetChars2000Per-topic char cap fed to relevance selection (≥200).
extractionDebounceMs60000Idle debounce before an extraction pass runs.
extractionLookback40Recent events scanned per pass (5–200).
llm.provider""Provider for extraction / relevance ranking (empty → keyword-only).
llm.model""Model for extraction / relevance ranking.
llm.maxTokens1024Completion token cap for LLM calls.

Example entry:

- id: memory
  name: '@deepseek-ai/dsh-plugin-memory'
  config:
    enableEntryInjection: true
    enableRelevance: true
    enableExtraction: true
    maxRelevant: 5
    relevanceTopK: 8
    relevanceBudgetChars: 2000
    extractionDebounceMs: 60000
    extractionLookback: 40
    llm:
      provider: deepseek   # example: fill in your route
      model: deepseek-chat
      maxTokens: 1024