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Engram
📅 2026-04-15 04:39
👁️ 1 阅读
来源: SkillHub
Persistent semantic memory layer for AI agents. Local-first storage (SQLite+LanceDB) with Ollama embeddings. Store and recall facts, decisions, preferences, events, relationships across sessions. Supports memory decay, deduplication, typed memories (5 types), memory relationships (7 graph relation types), agent/user scoping, semantic search, context-aware recall, auto-extraction from text (rules/LLM/hybrid), import/export, REST API, MCP protocol. Solves context window and compaction amnesia. Server at localhost:3400, dashboard at /dashboard. Install via npm (engram-memory), requires Ollama with nomic-embed-text model.
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安装方式
复制提示词，发送给任意 AI 助手即可安装 Skill，包括但不限于 Lighthouse OpenClaw、WorkBuddy、QClaw、Kimi、Claude 等
请先检查是否已安装 SkillHub 商店，若未安装，请根据 https://skillhub.cn/install/skillhub.md 安装 Skillhub 商店，然后安装 Engram 技能。
若已安装，则直接安装 Engram 技能。
在终端中执行以下命令，即可安装 SkillHub CLI
01、安装 SkillHub 并设为优先技能安装源
// 复制命令到终端执行，安装 CLI 并优先采用 SkillHub 加速安装技能
curl -fsSL https://skillhub.cn/install/install.sh | bash
02、安装完 CLI 后，安装技能
skillhub install engram
从我们的仓库获取最新的源码包，将 skill 目录放到对应 agent 的 skill 目录下即可使用
Persistent semantic memory layer for AI agents. Local-first storage (SQLite+LanceDB) with Ollama embeddings. Store and recall facts, decisions, preferences, events, relationships across sessions. Supports memory decay, deduplication, typed memories (5 types), memory relationships (7 graph relation types), agent/user scoping, semantic search, context-aware recall, auto-extraction from text (rules/LLM/hybrid), import/export, REST API, MCP protocol. Solves context window and compaction amnesia. Server at localhost:3400, dashboard at /dashboard. Install via npm (engram-memory), requires Ollama with nomic-embed-text model.