memohai / Memoh

[ English ] [ 简体中文 ] Memoh Multi-Member, Structured Long-Memory, Containerized AI Agent System. 📌 Introduction to Memoh - The Case for an Always-On, Containerized Home Agent [ Telegram Group ] [ Documentation ] [ Cooperation ] Memoh is an always-on, containerized AI agent system. Create multiple AI bots, each running in its own isolated container with persistent memory, and interact with them across Telegram, Discord, Lark (Feishu), Email, or the built-in Web/CLI. Bots can execute commands, edit files, browse the web, call external tools via MCP, and remember everything — like giving each bot its own computer and brain. Quick Start One-click install (**requires Docker**): *Silent install with all defaults: * Or manually: > **Install a specific version:** > > > **Use CN mirror for slow image pulls:** > > > On macOS or if your user is in the group, is not required. Visit after startup. Default login: / See DEPLOYMENT.md for custom configuration and production setup. Why Memoh? OpenClaw is impressive, but it has notable drawbacks: stability issues, security concerns, cumbersome configuration, and high token costs. If you're looking for a stable, secure solution, consider Memoh. Memoh is a multi-bot agent service built with Golang. It offers full graphical configuration for bots, Channels, MCP, and Skills. We use Containerd to provide container-level isolation for each bot and draw heavily from OpenClaw's Agent design. Memoh Bot can distinguish and remember requests from multiple humans and bots, working seamlessly in any group chat. You can use Memoh to build bot teams, or set up accounts for family members to manage daily household tasks with bots. Features • 🤖 **Multi-Bot Management**: Create multiple bots; humans and bots, or bots with each other, can chat privately, in groups, or collaborate. Supports role-based access control (owner / admin / member) with ownership transfer. • 👥 **Multi-User & Identity Recognition**: Bots can distinguish individual users in group chats, remember each person's context separately, and send direct messages to specific users. Cross-platform identity binding unifies the same person across Telegram, Discord, Lark, and Web. • 📦 **Containerized**: Each bot runs in its own isolated containerd container. Bots can freely execute commands, edit files, and access the network within their containers — like having their own computer. Supports container snapshots for save/restore. • 🧠 **Memory Engineering**: Multi-provider memory architecture — Built-in (off / sparse / dense modes), Mem0, and OpenViking. LLM-driven fact extraction, hybrid retrieval (dense semantic search + BM25 keyword + neural sparse vectors), 24-hour context loading, memory compaction & rebuild, and multi-language auto-detection. • 💬 **Multi-Platform**: Supports Telegram, Discord, Lark (Feishu), Email, and built-in Web/CLI. Unified message format with rich text, media attachments, reactions, and streaming across all platforms. Cross-platform identity binding. • 📧 **Email**: Multi-adapter email service (Mailgun, generic SMTP) with per-bot binding and outbound audit log. Bots can send and receive emails as a channel. • 🔧 **MCP (Model Context Protocol)**: Full MCP support (HTTP / SSE / Stdio). Built-in tools for container operations, memory search, web search, scheduling, messaging, and more. Connect external MCP servers for extensibility. • 🧩 **Subagents**: Create specialized sub-agents per bot with independent context and skills, enabling multi-agent collaboration. • 🎭 **Skills & Identity**: Define bot personality via IDENTITY.md, SOUL.md, and modular skill files that bots can enable/disable at runtime. • 🌐 **Browser**: Each bot can have its own headless Chromium browser (via Playwright). Navigate pages, click elements, fill forms, take screenshots (with annotated element labels), read accessibility trees, manage tabs, and more — enabling real web automation and AI-driven browsing. • 🔍 **Web Search**: 12 built-in search providers — Brave, Bing, Google, Tavily, DuckDuckGo, SearXNG, Serper, Sogou, Jina, Exa, Bocha, and Yandex — for web search and URL content fetching. • ⏰ **Scheduled Tasks**: Cron-based scheduling with max-call limits. Bots can autonomously run commands or tools at specified intervals. • 💓 **Heartbeat**: Periodic autonomous tasks — bots can perform routine operations (e.g., check-ins, summaries, monitoring) at configurable intervals with execution logging. • 📥 **Inbox**: Cross-channel inbox — messages from other channels are queued and surfaced in the system prompt so the bot never misses context. • 📊 **Token Usage Tracking**: Monitor token consumption per bot with usage statistics and visualization. • 🧪 **Multi-Model**: Works with any OpenAI-compatible, Anthropic, or Google Generative AI provider. Per-bot model assignment for chat, memory, and embedding. • 🖥️ **Web UI**: Modern dashboard (Vue 3 + Tailwind CSS) with real-time streaming chat, tool call visualization, in-chat file manager, container filesystem browser, and visual configuration for all settings. Dark/light theme, i18n. • 🚀 **One-Click Deploy**: Docker Compose with automatic migration, containerd setup, and CNI networking. Interactive install script included. Memory System Memoh's memory system is built around **Memory Providers** — pluggable backends that control how a bot stores, retrieves, and manages long-term memory. | Provider | Description | |----------|-------------| | **Built-in** | Self-hosted, ships with Memoh. Three modes: **Off** (file-based, no vector search), **Sparse** (neural sparse vectors via local model, no API cost), **Dense** (embedding-based semantic search via Qdrant). | | **Mem0** | SaaS memory via the Mem0 API. | | **OpenViking** | Self-hosted or SaaS memory with its own API. | Each bot binds one provider. During chat, the bot automatically extracts key facts from every conversation turn and stores them as structured memories. On each new message, the mo…