Memory

Local-first quick capture: select text in a DSH conversation to save it as a quote with its source (model and session), or jot quick notes from the sidebar; records stay in a local JSON file, with optional sync to a self-hosted service.

Backup and restore for dsh-mnemon: pick any of its three memory components (memory spaces, project documents, runtime memory) and archive them to S3-compatible storage or WebDAV, then browse the archives and restore a chosen subset. Live SQLite databases are copied through node:sqlite backup() so a concurrent writer cannot tear the copy; every file carries a SHA-256 checked before upload and again before restore; a restore previews by default and deletes the stale -wal/-shm sidecars before writing a database back. Archives are named mnemon-sync-<device>-<timestamp>.zip so backups from several machines stay tellable apart. Runs a single timer with intervals from hourly to weekly, stores credentials in a 0600 file outside the DSH profile, and depends on nothing outside Node.

Structural scaffolding for DSH agent continuity: layered memory (hot/index/judgments), judgment cards, handoff packs (compact mode), compaction review. Zero-dependency, pure files, portable — rebuild the 'self' across model changes. Not a memory engine; the skeleton of continuity.

Connects DSH Foxy to Foxy Memory for cross-platform recall, with local JSONL fallback, platform filters, and a memory browser. Requires dsh-foxy.

Approval-free memory archiving for DeepSeek Harness: writes Markdown memory files without approval prompts, backs the old file up before any overwrite, marks a revised conclusion as status: superseded in one call, and prunes old backups after 30 days by default (optional size cap). The writable scope is hard-limited to configured memory roots (default ~/.dsh/memory). Companion to dsh-kb-lite, which indexes these files and down-weights superseded ones. Host-only, no npm dependencies; requires Node.js 18+.

Memory engine for a long-lived companion agent: a six-module loop (gate, solidify, store, retrieve, inject, decay) that decides what is worth keeping, distils raw turns into long-term entries, fuses short and long term at recall time, and fades entries that stop being used. Runs offline by default; if DEEPSEEK_API_KEY is set it also sends each message to the DeepSeek API to judge and distil it. Zero runtime dependencies and no build step; ships three switchable panels over the same store - neural brain, memory ring and memory galaxy - so you can watch what it remembers. Non-commercial license: commercial use needs the author's permission.

Visualizes all DSH session memories as an interactive 3D nebula, with a neuron-signal skin, memory-scaled clusters, zoom-driven detail levels and a live write/read activity stream over SSE.

Cross-session error lessons for DSH agents: search past mistakes before handling errors and reuse their verified fixes.

Three-tier memory (personal, project, session) built on the Hy-Memory engine, with relevant memories injected before each step. Ships seven memory tools (search, add, list, get, update, delete, forget), a settings panel with per-tier lists, editing, change history and duplicate cleanup, real token accounting per write, session summaries written by the engine at session end, and a user profile refreshed from recent memories. Memories can be exported to and imported from MemHub. Needs Python 3.11+ once to install the engine, or uv, which fetches 3.12 itself; uninstalling keeps the stored memories.

What it does while she sleeps, in one card. Two things: (1) tidy the element memory — merge synonyms only when the model agrees, trim descriptions, prune weak links, propose analogies for the user to confirm, with a backup before every write and a 15%-of-library cap per pass; (2) dream — stitch her own past experiences (plus props from the element memory) into a short 3–6 sentence story, leave one line on her desk as a note labelled "this is a dream, not something that happened". The dream lives in its own file and never enters her memory or her personality prompt. Requires @ssamurias/dsh-fish for her event stream and dsh-memory-brain for the element library; model-approved merges and dreams need a local Ollama model (or a paid API key).

She keeps the questions your chats left unanswered, then goes and looks them up later. A line she asked you that ended in "?" and never got an answer is stored as a hanging question; on a schedule inside a daily window (08:00–23:00, five a day by default; an optional mouse/keyboard-idle gate is off by default) she picks the oldest one, searches the web and Bilibili, reads what is actually readable, distils it into two or three sentences and leaves a note on her desk. Questions about its own plugins are skipped and left for you. Read-only on her events: nothing is written to her memory, her growth is untouched, and dsh-fish needs no patching. Requires the @ssamurias/dsh-fish persona plugin for her event stream and a local Ollama model; a search API key is optional.

Object memory for DSH: each object is broken into fourteen kinds of smallest elements (shape, material, state, part, function...), observed links are stored apart from inferred ones, and analogies stay as questions until the user answers.

Rui Xi's Memory (dsh-memory-v2) — a local long-term memory plugin for DeepSeek Harness: four memory collections (semantic / conclusion / profile / temporary), per-day scene archives, two-phase consolidation and literal trace. When structured recall finds nothing, it falls back to searching the daily scene archive: time-window first (yesterday / last week / N days ago / dates), then a 2/7/30/180-day tiered sweep, with line-numbered citations. All data stays in the local DSH directory; semantic recall, diagnostic logs and the sensitive debug route are off by default.

Connects DeepSeek Harness to the hosted Renor memory MCP server over Streamable HTTP, using a Renor API key from RENOR_API_KEY, so the model can call Renor's recall and save tools. It is a configuration bundle with no code of its own.

Five-layer persona (L1–L5), event memory with FTS5 plus Dice retrieval, cognitive filter, skill cards with auto-frozen asset packs, millisecond reflex rules, three-tier safety degradation, a read-only brain star map, and an optional VPet-Simulator MOD bridge.

Private relationship notebook: scores each day of chat from message-level evidence and tracks how the relationship develops over time. Chats, profiles and drafts stay in your browser's local IndexedDB and the plugin runs no server of its own, but using model replies, profiling or automatic analysis sends the relevant chat context to the model service configured in DSH.

Elysia's memory plugin for dsh. One shared, human-editable MEMORY.md across every session: two-disk mirror, history snapshots, cross-process write lock; entries tier between the main file and a searchable archive by hit frequency; retrieval is keyword co-occurrence plus BM25. Nine sections (persona, requirements, corrections, lessons, methods, requests, sessions, method library, ingested docs) plus a dedicated self-identity section for a character's own self-cognition, injected above the persona. Ships an opt-in memory pack (packs/elysia: 61,903-char identity + 2,482-char persona, distilled from 1,696 officially-confirmed voice lines and checked against a 112,175-line game-dialogue corpus) that is off by default, backs up before writing, only touches identity/persona, and can be uninstalled. Also a skills library and a sticker library (you import your own images; none are bundled) that sends a fitting sticker at the right moment. On by default: a text bubble with her avatar after each reply, which costs one extra small model request unless the agent already announced (voice.bubble: false turns it off). Opt-in voice playback needs a local GPT-SoVITS engine (about 27 GB, installed separately, NVIDIA GPU required; the plugin downloads about 200 MB of weights) and is Windows-only; the automatic second-drive mirror is Windows-only too (elsewhere set mirrorPath, otherwise there is no mirror).

勿忘我：给任何 LLM 用的封存式记忆大脑——艾宾浩斯遗忘、联想召回、可塑性性格、自动总结，附 3D 莫比乌斯记忆星环与脑图。DeepSeek Harness 插件 / MCP / REST

DSH 本地记忆插件：自动记忆、遗忘曲线、关键词关联、可检索可编辑，数据留在本机。

Per-Bot memory for Tobs Bots (requires DeepSeek Harness with @botharness/core; it ships off with no Bots listed, and after you list a Bot and set mode to on it works with no other service): a read-only local full-text index of that Bot's own past conversations (Chinese words found inside sentences), memory imported from other AI tools, a status tool, optional auto recall before a step in which a Human speaks, and a service for other plugins. Richer backends can be chosen at install, with a quote first and a daily token cap: a public fact store (memv2-lite), the official Graphiti graph, or both, fed from the Bot's own conversations.

Cross-session long-term memory for DSH: eight memory layers, four notebooks, hybrid SQLite FTS5/vector/graph retrieval, agent-driven automatic capture, write lifecycle hooks, optional write audit, project spaces, forgetting and a visual management page. Full FTS5/vector/graph retrieval needs the bundled Go service, which ships only as a Windows x64 prebuilt; on macOS/Linux, build it from source or the plugin falls back to Node SQLite without FTS5 and retrieval degrades.

Sync a git-backed memory folder with a peer machine every time DeepSeek Harness starts — no daemon, no cron, no manual pull.

Bridges the shared ~/.agentloom store between DeepSeek Harness and Codex: injects the shared memories and the AGENTS.md entries the context budget truncates into the system prompt, and adds six loom_* tools for status, sync, memory search/list/add and skill listing. Requires the agentloom CLI installed and a one-time agentloom init; the seven-tool MCP bridge in the same repo is a separate package for MCP clients.

A cross-workspace Library for DeepSeek Harness: agents record files, tools, environments, knowledge and work records so any later session can index, search and reuse them.