NattoCB/dsh-plugin-memory ↗★ 0
@deepseek-ai/dsh-plugin-memory
Persistent 5-layer memory system for DeepSeek Harness (entry injection, relevance retrieval, agent tools, and LLM-backed auto-extraction).
安装
$
npx -p @deepseek-ai/dsh dsh plugin --profile web add github:NattoCB/dsh-plugin-memory说明文档
阅读完整 README ↗Configuration
Deploy via a DSH plugin entry (see package.json exports):
- id: memory
name: '@deepseek-ai/dsh-plugin-memory'
config:
enableEntryInjection: true # prepend the how-to-save + index block each session
enableRelevance: true # append relevant topic files per step (data-role=memory)
enableExtraction: true # idle-time LLM auto-extraction
maxRelevant: 5 # max files surfaced per step
relevanceTopK: 8 # max candidates the LLM selector may pick from
relevanceBudgetChars: 2000 # per-topic char cap fed to relevance/selector
extractionDebounceMs: 60000 # idle debounce before a pass runs
extractionLookback: 40 # recent events scanned for a pass
llm: # optional; omit provider/model to use keyword-only relevance + no extraction
provider: deepseek
model: deepseek-chat
maxTokens: 1024
Without an llm route, the plugin still provides index+topics, entry injection, keyword relevance, the agent tools, and profile rotation — only LLM-based extraction and LLM relevance ranking are disabled.