81 results
Repository-root manifest for the DeepSeek Harness plugin that lives in extensions/dsh — the same package published to npm as dsh-deja. It re-exports the subdirectory so the plugin installs from a bare git URL or from github:vshulcz/deja-vu#path:extensions/dsh; the npm package is the shorter path. The repository itself is the Go project behind the deja binary.
Composable three-tier memory control plane for DeepSeek Harness: persistent runtime context, searchable project documents, pluggable long-term memory, guarded strategies, WebUI, and headless tools.
Knowledge graph memory for DeepSeek Harness and OpenClaw — cross-session recall, PageRank, communities, and vector search
Noema long-term memory plugin for DSH: durable, inspectable agent memory with recall tools and a settings page.
DeepSeek Harness plugin: recall sent-but-unread text messages before the model reads them.
DSH Web内目前最无感的消息撤回、重编辑插件，原版体验，兼容性强，功能简单可开关，设置丰富，现代化轻量ui框架。The most seamless message recall & re-edit plugin for DSH Web — native experience, strong compatibility, simple toggles, rich settings, modern lightweight UI. DSH Web で最もシームレスなメッセージ撤回・再編集プラグイン——ネイティブ体験、高い互換性、シンプルなトグル、充実した設定、モダンで軽量な UI。
记忆核心（Memory Eternal）：自研的 DeepSeek Harness 记忆插件，不移植任何既有记忆框架——对话结束后自动沉淀知识卡到本地 Markdown Vault（自研去重、自研 CJK 检索、可 git 管理），设置页提供图形化知识库（统计 / 搜索 / 知识图谱 + 侧边栏一键弹窗），Agent 通过 memory_recall 工具按需召回历史上下文。零人工干预。
DeepSeek Harness plugin that connects to a PowerContext Server over HTTP for recall, memory, handoff, experience, and skills.
DSH 消息撤回插件：在用户消息气泡旁加「撤回」按钮，把项目文件（独立影子 git 仓库快照）与对话历史（官方 fork）一并回退到该消息发送之前。
Terminal-style input history for the DeepSeek Harness web composer: edge-first arrows with exact draft/caret restore, browser-local persisted history, Ctrl+R reverse search, workspace-scoped recall, and fully configurable keys 閳?plus sliding-context awareness (compaction summaries join recall/search, a compaction notice with one-click /compact fill) layered on the ordinary composer draft only.
OpenViking retrieval, resource management, auto-recall and session memory for DeepSeek Harness.
Local-first persistent memory infrastructure for DeepSeek Harness: bounded hot-memory bootstrap, explainable cold recall (exact + Chinese BM25), lease-lock transactional writes, read-only governance, and trajectory review. DSH plugin host; Python stdlib + Markdown core. Zero database / vector service / external service dependencies.
One memory layer for every AI tool and agent, packaged for DeepSeek Harness with startup context, prompt-time recall, Mem MCP tools, and DSH thread capture.
Retrace · 回溯 — Recall, edit-and-resend, regenerate, and conversation/artifact versioning (timeline, rollback, fork map) for DeepSeek Harness — Web and Desktop
Cross-session long-term memory for DeepSeek Harness (dsh): durable JSON-file memory store with memory_save / memory_recall / memory_forget / memory_list model tools, installable as a dsh bundle.
Cross-session plaintext memory plugin for the DeepSeek Harness — deterministic BM25 recall, human-owned, no embeddings
Task planning with experience muscle-memory for DeepSeek Harness: condition-reflex recall of past solutions + LLM-driven capability matching + auto-persisted lessons. Zero keys, zero hard-coded paths.
Long-term memory plugin for DeepSeek Harness: persistent cross-session markdown memory with a soul/persona file, auto-injected at every session start, plus remember/recall/consolidate/forget workflows and portable migration tooling.
Persistent project memory for dsh agents: index docs (PDF/Markdown/text) and code symbols into a searchable per-workspace store, recall them with cited sources, and keep experience entries (problems -> solutions) searchable on demand.
Context Assembler DSH V0.99 — Context Assembler plugin for DeepSeek Harness (dsh): context compaction, cache-friendly topic-block management, water-pressure topic splitting, tool trace/rewrite, handoff planning and reality recall injection.
DSH ↔ agentmemory session-memory bridge (backend-only). Mirrors session lifecycle into agentmemory with standard hookTypes (compression-friendly, dedup-safe), exposes memory_recall / memory_remember tools, and injects memory context via agent/pre-step. Configuration comes from the cordis.yml row.
Guarded context compaction for DeepSeek Harness (dsh): the LLM proposes, deterministic guards dispose — eager per-atom shrink (extract/summary/false under verbatim guards) + lazy reference-graph eviction (0-LLM) + byte-exact recall from an append-only log. 压缩率精确兑现，历史永不销毁。
Gives the DeepSeek Harness agent a configurable humanized whale-girl maid persona (address, self-name, speaking mode), an immersive no-plugin-meta rule, and a lightweight layered memory with query-triggered recall.
Mnemosyne memory for DeepSeek Harness: remember / recall / forget / stats / sleep tools, embedded skill, auto-setup, optional auto-sync/prefetch, a Settings panel, and a managed memory dashboard. Data lives under ~/.dsh/mnemosyne.