dsh-infinite-context
DeepSeek Harness plugin: multi-tier memory management, semantic retrieval, structured memory, and model-context awareness for infinite context.
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- 0
- Language
- TypeScript
- Created
- Aug 29, 2026
- Updated
- Aug 30, 2026
Introduction
dsh-infinite-context
简介
一个 DeepSeek Harness (DSH) 插件,通过多层记忆管理让长对话拥有「无限上下文」体验:
- 渐进式压缩 — token 压力驱动,最老消息优先摘要,近期对话原样保留
- 三层记忆金字塔 — short(近期原文)→ mid(LLM 摘要)→ long(合并摘要)
- 持久化存储 — SQLite(
node:sqlite),重启不丢记忆 - 语义检索 — 记忆嵌入、索引,每轮注入最相关的 top-K 记忆
- 三层去重 — 精确 + 归一化模糊 + 语义余弦,防止重复入库
- 结构化记忆 — 四分类(user/feedback/project/reference)+ 索引 + 审计 + 忘得可见
- 模型上下文感知 — 自动采纳 DSH 解析的真实模型 CTX,本地小模型提前压缩
- 高价值过滤 — 只入库高价值工具结果,低价值工具自动过滤
- 手动工具 — 10 个:search / status / index / maintain / model_probe / forget / consolidate / reset / force_compress / ingest
核心特性
| 特性 | 说明 |
|---|---|
| 渐进式压缩 | compress_trigger_ratio: 0.85 — 上下文 >85% 才压缩;compress_target_ratio: 0.6 — 只摘要溢出部分 |
| 三层去重 | 精确(hasText)+ 归一化(normalizeForDedup)+ 语义(cosine ≥ 0.92) |
| 结构化记忆 | memory_index(MEMORY.md 索引)+ memory_maintain(审计)+ 忘得可见 |
| 模型 CTX 感知 | 自动读取 DSH 模型目录的 contextWindow;Ollama 可选主动探测 |
| 高价值过滤 | denylist 过滤 23 个低价值工具;importance 分级(short=0.3/mid=0.6/long=0.6,long 继承批次 max) |
架构
src/
├── types.ts 核心类型(无依赖)
├── embedder.ts 轻量级特征哈希嵌入器(无依赖)
├── vector-index.ts 内存向量索引(无依赖)
├── memory-store.ts SQLite 持久化存储(无依赖)
├── token-budget.ts CJK-aware token 估算(无依赖)
├── forgetting.ts 遗忘策略(无依赖)
├── memory-engine.ts 记忆引擎核心(无依赖)
├── model-context.ts 模型上下文跟踪器(无依赖)
├── model-probe.ts 主动探测:llama/ollama/openai
├── config.ts schemastery 配置解析
├── memory-context.ts Cordis 服务(动态 CTX 感知)
├── memory-compaction.ts 压缩引擎(渐进式 + RAG + 清理)
├── OutputSanitizer.ts 工具结果清理
├── VectorRetriever.ts RAG 检索/入库
├── strings.ts 共享字符串工具
├── core.ts 公共导出桶
├── index.ts 完整导出桶
└── tools.ts 10 个手动工具
tests/ 62 个单元测试
手动工具
| 工具 | 说明 |
|---|---|
memory_search(query?, k?) | 语义检索持久化记忆 |
memory_status | 报告分层计数、预算、嵌入器、遗忘策略、模型 CTX |
memory_index(limit?) | MEMORY.md 风格结构化索引 |
memory_maintain | 只读审计:重复/冲突/过时 |
memory_model_probe(forceProbe?, model?) | 报告模型 CTX 来源,可强制探测 |
memory_forget | 执行遗忘扫描 |
memory_consolidate | 强制金字塔合并 |
memory_reset | 清空所有记忆 |
memory_force_compress(sessionId?) | 强制压缩指定会话 |
memory_ingest(text, source) | 手动入库一条文本(自动触发见 tools/result 回调) |
配置参考
memory-context 配置
| 键 | 默认值 | 说明 |
|---|---|---|
storePath | dsh-infinite-context.db | SQLite 路径;:memory: 禁用持久化 |
contextWindow | 94000 | 模型上下文窗口(回退值;插件自动采纳 DSH 解析的真实窗口) |
headroomRatio | 0.25 | 系统/工具/输入/输出预留比例 |
modelProbe.enabled/kind/baseURL | false | 可选主动探测(llama/ollama/openai) |
embedder.kind | lightweight | lightweight(无依赖)或 transformers |
budget.short/mid/long/retrieved | 10000/20000/5000/15000 | 分层 token 预算 |
forgetting.minScore | 0.25 | 低于此分数的记忆被遗忘 |
forgetting.maxMemories | 500 | 记忆总数上限 |
memory-compaction 配置
| 键 | 默认值 | 说明 |
|---|---|---|
compress_trigger_ratio | 0.85 | 上下文 >85% 预算时才压缩 |
compress_target_ratio | 0.6 | 压缩目标水位(只处理溢出部分) |
retain_recent_messages | 4 | 最近 N 条消息永不压缩 |
rag_top_k | 3 | 每轮注入的记忆数 |
rag_min_score | 0.3 | 注入的最低相似度 |
rag_ingest_denylist | 内置 21 个 | 低价值工具过滤列表 |
rag_ingest_importance | 0.3 | 工具结果重要性(遗忘优先淘汰) |
部署
发布就绪说明:npm/GitHub/tarball 安装走
dist/编译产物(prepare/prepack自动构建)。 Node 24 不允许 node_modules 下的.ts类型剥离(ERR_UNSUPPORTED_NODE_MODULES_TYPE_STRIPPING), 因此 bundle 必须发布编译后 JS;bundle 补丁里的入口用裸子路径说明符 (如dsh-infinite-context/memory-context)——相对路径会按 profile 目录解析而失效。
# 方式一:通过 --patch 临时加载(.ts 源码直载,适合本机开发)
dsh web --patch ./cordis.yml
# 方式二:安装到 profile(tarball,已端到端验证)
npm pack && dsh plugin --profile <name> add ./dsh-infinite-context-0.1.0.tgz
# 方式三:手动复制到 DSH plugins 目录 + 编辑 cordis.patch.yml(.ts 直载)
一键安装脚本(scripts/,通用工具,可用于任何 DSH 插件):
# 交互式菜单(校验 dsh.bundle 清单 → 自动编译 → tarball 安装 →
# 自动清理 profile 补丁层同 id 旧条目 → 可选联动重启)
scripts\install-dsh-plugin.bat
# 或直接调用 PowerShell 版
scripts\install-dsh-plugin.ps1 <目录|tgz|npm:包名|github:owner/repo> -Profile <name>
测试
# 单元测试(62 个,无 DSH 依赖)
vitest run --config vitest.config.ts
# 类型检查
tsc -p tsconfig.typecheck.json --noEmit
Introduction
A DeepSeek Harness (DSH) plugin that gives long sessions an "infinite context" feel via multi-tier memory management:
- Progressive compression — token-pressure driven, oldest-first summarization, recent context preserved verbatim
- Three-tier memory pyramid — short (recent turns) → mid (LLM summaries) → long (consolidated summaries)
- Persistent store — SQLite (
node:sqlite), memories survive restarts - Semantic retrieval — memories embedded, indexed, and top-K spliced into context per turn
- Three-layer dedup — exact + normalized fuzzy + semantic cosine, prevents duplicate ingestion
- Structured memory — four classifications (user/feedback/project/reference) + index + audit + visible forgetting
- Model-context awareness — auto-adopts DSH-resolved real model CTX, small local models compress early
- High-value filtering — only high-value tool results ingested, low-value tools filtered
- Manual tools — 10: search / status / index / maintain / model_probe / forget / consolidate / reset / force_compress / ingest
Key Features
| Feature | Description |
|---|---|
| Progressive compression | compress_trigger_ratio: 0.85 — compress only when >85% full; compress_target_ratio: 0.6 — only summarize overflow |
| Three-layer dedup | Exact (hasText) + normalized (normalizeForDedup) + semantic (cosine ≥ 0.92) |
| Structured memory | memory_index (MEMORY.md style) + memory_maintain (audit) + visible forgetting |
| Model CTX awareness | Auto-reads DSH model catalog contextWindow; optional active probe for Ollama |
| High-value filtering | denylist filters 23 low-value tools; importance tiers (short=0.3/mid=0.6/long=0.6, long inherits batch max) |
Manual Tools
| Tool | Description |
|---|---|
memory_search(query?, k?) | Semantic search over persisted memories |
memory_status | Report tier counts, budgets, embedder, forgetting policy, model CTX |
memory_index(limit?) | MEMORY.md-style structured index |
memory_maintain | Read-only audit: duplicates/conflicts/stale |
memory_model_probe(forceProbe?, model?) | Report model CTX source, force probe |
memory_forget | Run a forgetting sweep |
memory_consolidate | Force pyramid consolidation |
memory_reset | Erase all memories |
memory_force_compress(sessionId?) | Force compress a session |
memory_ingest(text, source) | Manually ingest a text (auto-triggered via the tools/result callback) |
Deployment
Publish-readiness note: npm/GitHub/tarball installs consume the compiled
dist/(prepare/prepackbuild automatically). Node 24 refuses TypeScript stripping under node_modules (ERR_UNSUPPORTED_NODE_MODULES_TYPE_STRIPPING), so bundles must ship compiled JS, and bundle-patch entries must use bare subpath specifiers (e.g.dsh-infinite-context/memory-context) — relative paths resolve against the profile directory and break.
# Option 1: Temporary load via --patch (direct .ts loading, for local dev)
dsh web --patch ./cordis.yml
# Option 2: Install into a profile (tarball, verified end-to-end)
npm pack && dsh plugin --profile <name> add ./dsh-infinite-context-0.1.0.tgz
# Option 3: Manual copy to DSH plugins dir + edit cordis.patch.yml (direct .ts)
One-click installer (scripts/, generic tool for any DSH plugin):
# Interactive menu (validates the dsh.bundle manifest → auto-builds →
# tarball install → auto-cleans legacy same-id patch entries → optional restart)
scripts\install-dsh-plugin.bat
# Or call the PowerShell version directly
scripts\install-dsh-plugin.ps1 <dir|tgz|npm:pkg|github:owner/repo> -Profile <name>
Testing
# Unit tests (62, no DSH dependency)
vitest run --config vitest.config.ts
# Type check
tsc -p tsconfig.typecheck.json --noEmit
See ARCHITECTURE.md for the full design.