# EchoMuse **Repository Path**: tutuHM/echo-muse ## Basic Information - **Project Name**: EchoMuse - **Description**: 零云端、本地优先的桌面 AI 助手 — 聊天 · 角色扮演 · 学习工具 · 知识库，一个应用全搞定 - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: main - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 1 - **Forks**: 0 - **Created**: 2026-02-25 - **Last Updated**: 2026-03-30 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README

EchoMuse — Local-First AI Desktop Assistant

EchoMuse

Your Private, Local-First AI Desktop Assistant
Chat · Roleplay · Study Tools · Knowledge Base · MCP Tools — All in One App

Quick Start · Features · Download · 国内下载

--- ## Why EchoMuse? / 为什么选 EchoMuse？ > **Zero cloud dependency. Your data never leaves your machine.** Most AI chat apps force you to pick a lane — casual chat, roleplay, or productivity. EchoMuse doesn't. It's a single lightweight desktop app that handles **daily conversations, deep character roleplay, academic study tools, and document-powered knowledge retrieval** — all running locally on your machine with optional cloud API support. > **零云端依赖，数据始终留在本地。** > > 大多数 AI 聊天工具只能做一件事。EchoMuse 不一样 — 日常聊天、深度角色扮演、学习工具、知识库检索，一个桌面应用全部搞定，本地运行，也可接入云端 API。 --- ## Screenshots / 界面预览

Chat Interface Character Cards

Knowledge Base Settings

--- ## Features / 功能亮点 ### 🤖 Connect Any LLM / 接入任意模型 Run **Ollama models locally** (Qwen3, Mistral, Llama, etc.) or connect to **7+ cloud APIs** (OpenAI, DeepSeek, Kimi, Claude, SiliconFlow, Zhipu, Baichuan) — or mix both. Every model supports **Flash** (fast response) and **Thinking** (deep reasoning with chain-of-thought) dual modes. 本地 Ollama 模型 + 7 种以上云端 API，可混合使用。每个模型支持 Flash（快速）和 Thinking（深度推理）双模式切换。 ### 💬 Smart Conversations / 智能对话 - **Multi-session management** with search, favorites, and auto-titling - **Message branching** — regenerate or edit any message to create tree-structured conversation paths - **Web search injection** — DuckDuckGo results fed directly into context - **Real-time translation overlay** — translate AI replies into 8 languages while keeping the original 多会话管理 · 消息分支（树状对话） · 联网搜索注入 · 实时翻译覆盖层（8 语言） ### 🎭 Deep Roleplay System / 深度角色扮演 - **Custom characters** with avatars, expressions, memory text, and relationship settings - **Tavern card import** — drag-and-drop PNG/JSON character cards - **Lorebook** — keyword-triggered world-building lore auto-injected into context - **Multi-character group chat** with spectator mode - **Message branching** for exploring different story paths 自定义角色卡 · Tavern 卡导入 · Lorebook 世界观书 · 多角色群聊 · 旁观模式 · 剧情分支探索 ### 📚 Knowledge Base (RAG) / 知识库检索 Upload documents (txt / md / pdf / docx) → automatic chunking → **BM25 + vector hybrid retrieval**. Toggle it on in any chat and the AI answers with your documents as context. 上传文档自动分块索引，BM25 + 向量混合检索，聊天中一键启用。 ### 🔧 MCP Tool Integration / MCP 工具集成 Connect external **MCP servers** (stdio / SSE / HTTP) to extend the AI's capabilities — web scraping, sequential thinking, note-taking, and more. Supports multi-turn automatic tool calling. 接入外部 MCP 服务器，扩展 AI 能力 — 网页抓取、深度推理、笔记等，支持多轮自动工具调用。 ### 🎓 Study Tools / 学习工具 - **Exam Review Pack Generator** — outlines, key points, question banks (MCQ / fill-in / short answer), Anki flashcard export - **Paper & Report Generator** — lab reports, course papers, structured academic writing 期末复习包生成器（大纲 + 题库 + Anki 卡片） · 论文/实验报告生成器 ### 🔊 Voice / 语音 - **TTS** — AI reads replies aloud with configurable voice packs - **STT** — browser speech recognition + local Whisper offline transcription TTS 语音朗读 + 本地 Whisper 语音输入 ### 📤 Export & Share / 导出与共享 - Export to **JSON / Anki CSV / PDF / Word** - **Team sharing** — OpenAI-compatible API relay with member tokens and usage tracking - **LAN access** — QR code for mobile/tablet access over local network 多格式导出 · 团队共享（OpenAI 兼容中继） · 局域网 QR 码访问 ### 🌍 Polished Experience / 精致体验 - **8 languages** — Chinese, English, Japanese, Korean, French, German, Spanish, Russian - **3 themes** — Light, Dark, System auto - **First-run setup wizard** — guided onboarding for beginners - **PWA support** — also works as a web app in your browser 8 语言 UI · 3 种主题 · 新手引导向导 · PWA 支持 --- ## Quick Start / 快速开始 ### Option 1: Download Installer (Recommended) > Go to [GitHub Releases](https://github.com/YPDWHM/EchoMuse/releases) or [Gitee Releases (国内)](https://gitee.com/tutuHM/echo-muse/releases) and grab the latest `.exe` — NSIS installer or portable version. ### Option 2: Run from Source ```bash git clone https://github.com/YPDWHM/EchoMuse.git cd EchoMuse npm install # Web version (local only) npm run local # Desktop version (Electron) npm run desktop:dev ``` > Gitee 用户：`git clone https://gitee.com/tutuHM/echo-muse.git` > LAN sharing: `npm run share` ### Option 3: Windows One-Click Bootstrap ```bash npm run bootstrap:win ``` --- ## Model Setup / 模型配置 EchoMuse works with both local and cloud models — use one or both. ### Local Models (Ollama) Install [Ollama](https://ollama.com), then pull a model: ```bash ollama pull qwen3:8b # Recommended — 8B general purpose ollama pull mistral:7b # Alternative — fast and lightweight ``` ### Cloud APIs Add a Provider in Settings. Supported: | Provider | Notes | |:---|:---| | OpenAI | GPT series | | DeepSeek | Cost-effective | | Kimi (Moonshot) | Long context | | SiliconFlow | China-optimized CDN | | Zhipu AI | GLM series | | Baichuan | Chinese-optimized | | Anthropic | Claude series | | Custom | Any OpenAI-compatible endpoint | --- ## Architecture / 架构 ```mermaid graph LR subgraph Frontend A[Vanilla JS SPA] --> B[Chat UI] A --> C[Settings] A --> D[Artifact Drawer] end subgraph Backend E[Express Server] E --> F[Ollama Local] E --> G[Cloud APIs] E --> H[MCP Manager] E --> I[RAG Engine] E --> J[Translation] E --> K[Team Relay] end A <-->|HTTP + SSE| E subgraph Desktop L[Electron Shell] --> E end ``` --- ## Tech Stack / 技术栈 | Layer | Tech | |:---|:---| | Frontend | Vanilla JS, KaTeX, Marked | | Backend | Node.js, Express | | Desktop | Electron | | LLM | Ollama, OpenAI API, Anthropic API | | Retrieval | BM25 + Vector Embedding (Cosine Similarity) | | Tools | MCP (Model Context Protocol) | | Export | jsPDF, docx, html2canvas | --- ## Project Structure / 项目结构 ``` EchoMuse/ ├── server.js # Express backend (API, LLM, RAG, MCP, translation, team sharing) ├── mcp-manager.js # MCP client connection manager ├── public/ │ ├── index.html # Main page │ ├── app.js # Frontend logic │ ├── styles.css # Styles (light/dark themes) │ └── js/ # Modular JS (utils, domain, chat render, voice, setup wizard) ├── desktop/ │ ├── main.js # Electron main process │ └── preload.js # Electron preload ├── prompts/ # Prompt templates └── scripts/ # Startup & build scripts ``` --- ## FAQ / 常见问题 **Q: I don't know which model to pick. / 不懂选什么模型？** Add a cloud API Provider in Settings (e.g. DeepSeek) — no local model needed. 在设置里添加云端 API Provider（如 DeepSeek），不装本地模型也能用。 **Q: Can my PC run local models? / 电脑能跑本地模型吗？** 16GB RAM can handle 8B models (qwen3:8b, mistral:7b). 13B+ needs better hardware. 16GB 内存可跑 8B 级别模型，更大模型需要更好配置。 **Q: How to import character cards? / 怎么导入角色卡？** Sidebar → Contacts → Import Card. Supports PNG (embedded data) and JSON. 侧边栏「联系人」→「导入卡片」，支持 PNG 和 JSON 格式。 **Q: How to share with others on LAN? / 怎么局域网共享？** Enable Team Sharing in Settings, generate member tokens, others connect via your LAN IP. 设置里开启「团队共享」，生成成员 Token，对方通过局域网 IP 访问。 --- ## Contributing / 参与贡献 Issues and feature requests are welcome on [GitHub](https://github.com/YPDWHM/EchoMuse/issues) or [Gitee](https://gitee.com/tutuHM/echo-muse/issues). 欢迎在 GitHub 或 Gitee 提交 Issue 和功能建议。 --- ## License [EchoMuse Source Available License](LICENSE) — Free for personal, educational, and non-commercial use. Commercial use requires author authorization. 个人使用、学习、教育用途免费。商业用途需获得作者授权。 ---

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