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dsh-tdai-memory

Tdai Memory

TencentDB Agent Memory port for DeepSeek Harness: L0 conversation capture → L1 structured memory extraction → L2 scenarios/L3 profiles, automatic recall injection + memory/conversation search tools; reuses existing ~/.memory-tencentdb/memory-tdai data; includes a Web UI settings panel.

The plugin will be installed here. Keep web if you are unsure.

npx -y @deepseek-ai/dsh plugin --profile web add dsh-tdai-memory@0.4.6
READMECompatibilityVersions

Compatibility and provenance

Tdai Memory is published as dsh-tdai-memory and currently resolves to version 0.4.6. The Hub verifies its manifest and preserves the exact installation source for reproducible installs.

DSH compatibility
*
Runtime surfaces
web
Release source
npm
Registry updated
11/4/2026

Versions

0.4.6stable
10/31/2026
0.4.5stable
10/24/2026
0.4.4stable
10/17/2026
Show 17 more versionsCollapse versions
0.4.3stable
10/17/2026
0.4.2stable
10/4/2026
0.4.1stable
9/30/2026
0.4.0stable
9/30/2026
0.3.6stable
9/29/2026
0.3.5stable
9/25/2026
0.3.4stable
9/24/2026
0.3.3stable
9/22/2026
0.3.2stable
9/10/2026
0.3.1stable
9/10/2026
0.3.0stable
9/3/2026
0.2.14stable
8/24/2026
0.2.13stable
8/21/2026
0.2.12stable
8/21/2026
0.2.11stable
8/21/2026
0.2.10stable
8/16/2026
0.2.9stable
8/16/2026

Related plugins

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Latest
0.4.6
DSH
*
HMR
Process restart
Tree shaking
Safe tree shaking not declared
Unpacked size
736.6 kB
Files
76
Surface
web
License
MIT
Source
npm
GitHub
★ 9
Weekly downloads
852
Security scan
✓ v0.4.6 scan passed
Last push
10/31/2026
View source ↗Project homepage ↗
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README

DSH TDAI Memory

简体中文 | English

将 TencentDB Agent Memory 的分层记忆系统接入 DeepSeek Harness:捕获对话、提取结构化记忆,并在后续对话中检索相关内容。项目基于原 OpenClaw 插件的核心进行 DSH 适配。

功能

层级用途
L0捕获原始对话,供后续检索
L1使用提取模型整理事实、偏好和事件等结构化记忆
L2 / L3生成场景信息与用户画像
召回与搜索按当前消息召回相关记忆;提供 tdai_memory_search 和 tdai_conversation_search 工具

数据默认保存在 ~/.memory-tencentdb/memory-tdai,可复用已有同目录记忆。记忆写入、提取和召回依赖启用状态、模型连接及检索结果,不保证每条信息都会被保存或召回。

兼容性与安装

支持 DSH Web / Desktop;仓库声明兼容 0.2.0-rc.2、0.2.1-rc.1 / rc.2 / rc.3 / rc.4 / rc.5 和符合 >=0.2.0-rc.2 <0.3.0 的版本,预发布版本范围见 package.json。要求 Node.js >=22.18。

Desktop 先在 应用 → 管理 dsh 命令 安装桌面版 dsh:

dsh plugin --profile desktop add dsh-tdai-memory

Web 将 desktop 改为 web。安装后重启 DSH,打开 插件 → 已安装 → dsh-tdai-memory。也可通过 Enhancement Suite 安装。

快速配置

  1. 配置用于记忆提取的 OpenAI 兼容 LLM 地址、模型和密钥。
  2. 配置 OpenAI 兼容 Embedding 地址、模型和维度。默认地址 http://127.0.0.1:8088/v1 只是配置值,你需要自行提供可用的 Embedding 服务。
  3. 选择自动记忆并保存,重启 DSH 使记忆管线配置生效。
  4. 对话后可让 Agent 搜索记忆,或检查插件日志确认提取和工具注册情况。
模式捕获提取自动召回搜索工具
自动记忆开开开开
仅搜索已有记忆关关关开
暂停记忆功能关关关关

高级设置可单独调整开关、存储位置和调优参数;已有混合配置显示为自定义组合,不会自动覆盖。搜索工具开关可即时生效,其他管线配置按提示重启。表单只写入编辑过的字段,未修改的密钥保留。

使用说明

  • 提取模型需要稳定输出结构化结果;提取在后台进行,耗时和质量取决于模型与服务。
  • 默认关闭 LLM 去重。默认 Embedding 使用本地 OpenAI 兼容端点;远程兼容端点不需要 node-llama-cpp。若选择完全本地的 Embedding 后端,需要在目标 Profile 另行安装并批准可选的 node-llama-cpp 构建。
  • 搜索工具缺失时,确认工具开关已开启,并检查 [tdai-memory] tools registered 日志。语言跟随 DSH。
  • 捕获的对话和记忆会保存在本机;提取与 Embedding 请求会发送到你配置的服务,请自行选择合适的端点并备份数据。

开发、来源与反馈

  • 历史详细文档保留架构、配置示例和旧版说明,其中安装命令与兼容性信息可能已过时。
  • 本项目移植 TencentDB Agent Memory;随仓库分发的第三方代码和许可证请参见对应目录。
  • npm · 问题反馈 · MIT License