
chatless
💻一款简洁实用轻量级的本地AI对话客户端,采用Tauri2.0和Next.js编写 A simple, practical, and lightweight local AI chat client, written in Tauri 2.0 & Next.js.
Stars: 212

Chatless is a modern AI chat desktop application built on Tauri and Next.js. It supports multiple AI providers, can connect to local Ollama models, supports document parsing and knowledge base functions. All data is stored locally to protect user privacy. The application is lightweight, simple, starts quickly, and consumes minimal resources.
README:
chatless 是一个基于Tauri和Next.js构建的AI聊天桌面应用。支持多种AI提供商,可连接Ollama本地模型,支持文档解析和知识库功能。所有数据本地存储,保护用户隐私。应用轻量简洁、启动快速、资源占用少。
中文 | English
功能 | 说明 |
---|---|
多 AI 提供商 | 内置适配 OpenAI、Anthropic、DeepSeek、Gemini 等主流云端模型,可一键切换 |
本地模型 | 通过 Ollama / LM Studio 运行 Llama2、Mistral、Qwen 等离线模型,无网络也可使用 |
文档与图片解析 | 支持 PDF / Word / Markdown 等文档解析及 Vision 图片分析 |
RAG 知识库 | 全本地向量索引,聊天时按需检索文档片段,提升回答准确性 |
Prompt 管理 | 用 / 快速插入常用提示词,统一管理、复用 |
MCP 服务 | 用 @ 调用 Model Context Protocol 服务器,集中管理第三方工具链 |
数据可携带 | 聊天、向量库、设置均以文件形式导入 / 导出,方便迁移备份 |
跨平台 | Windows / macOS / Linux 原生应用,体积小,性能好,启动快 |
点击对应链接进入下载页面,选择适合您系统的安装包:
- Windows: Chatless 安装包 - 选择 .exe 或 .msi 文件
- macOS: Chatless for macOS - 根据处理器选择 aarch64 或 x64 版本
- Linux: Chatless for Linux - 选择适合您发行版的 .rpm、.deb 或 .AppImage 文件
详细安装说明: 查看 完整安装指南 获取详细的安装步骤和常见问题解决方案
- 配置AI提供商 - 在设置中添加API密钥
- 设置本地模型 - 安装Ollama并下载模型(可选)
- 开始使用 - 选择模型开始对话或上传文档
git clone https://github.com/kamjin3086/chatless.git
cd chatless
pnpm install
pnpm tauri dev
- 配置AI提供商 – 在设置中添加API密钥,支持OpenAI、Anthropic、DeepSeek等
- 设置本地模型 – 安装Ollama并下载模型(可选,适合离线使用)
- 创建知识库 – 上传PDF、Word、Markdown等文档构建本地知识库
- 开始对话 – 选择AI模型开始智能对话
- 文档分析 – 上传图片或文档进行分析和问答
- 管理历史 – 查看和管理对话记录,支持搜索和导出
部分 Windows 环境可能因缺少 Microsoft Visual C++ 运行库而出现启动即退出/闪退。可按以下步骤修复:
- 下载并安装最新的 Microsoft Visual C++ 2015–2022 Redistributable (x64):
- 安装完成后重启应用(必要时重启系统)。
- 若仍有问题:
- 在「设置 → 应用 → 已安装的应用」中搜索"Visual C++ 2015-2022 Redistributable (x64)"确认已安装。
- 通过应用内「设置 → 反馈」提交日志与问题描述。
说明:应用依赖的原生库(如 Tauri/ONNX 等)在 Windows 上需要 MSVC 运行库支持,缺失时可能导致闪退。
感谢@ukhack
,在 https://github.com/kamjin3086/chatless/issues/23#issuecomment-3203662395 提供该方法
详细查看 chatless KanBan
- 前端: Next.js 15 + TypeScript + TailwindCSS
- 后端: Tauri 2.0 + Rust
- 数据库: SQLite
- AI集成: 多提供商支持 + Ollama本地模型
- 打开应用设置
- 进入"AI模型设置"选项卡
- 点击"管理提供商",新增需要的提供商,输入API密钥
- 配置密钥后自动拉取模型列表,可以在聊天界面开始与AI对话
提示: 支持多种AI提供商,可以同时配置多个,根据需要切换使用
如果您希望离线使用,可以配置本地模型:
# 1. 安装Ollama
curl -fsSL https://ollama.ai/install.sh | sh
# 2. 下载常用模型
ollama pull llama2:7b # 7B参数模型,适合一般对话
ollama pull mistral:7b # Mistral模型,性能优秀
ollama pull qwen:7b # 通义千问模型,中文支持好
# 3. 在应用设置中配置Ollama地址(默认:http://localhost:11434)
隐私优势: 本地模型确保所有对话数据不会离开您的设备
- 本地数据存储 – 所有对话和文档保存在本地设备
- 无数据上传 – 不向云端上传任何数据
- 开源透明 – 代码开源,可验证安全性
- 隐私保护 – 不收集用户个人信息
如果您在使用过程中遇到问题或有改进建议,欢迎通过以下渠道联系我们:
渠道 | 说明 | 链接 |
---|---|---|
GitHub Issues | 报告Bug、功能请求、问题反馈 | 提交Issue |
讨论区 | 功能讨论、使用交流、社区互动 | 参与讨论 |
应用内反馈 | 快速反馈、日志提交、问题描述 | 应用内设置 → 反馈 |
反馈建议: 提交问题时请尽可能详细描述问题现象、操作步骤和系统环境,这样我们能更快地帮助您解决问题
欢迎所有形式的贡献!
- Fork这个项目
- 创建你的功能分支 (
git checkout -b feature/AmazingFeature
) - 提交你的更改 (
git commit -m 'Add some AmazingFeature'
) - 推送到分支 (
git push origin feature/AmazingFeature
) - 打开一个Pull Request
本项目采用MIT许可证 - 查看LICENSE文件了解详情。
- Tauri – 跨平台桌面应用框架
- Next.js – React 全栈框架
- TailwindCSS – 实用优先的 CSS 框架
- Ollama – 本地大语言模型运行时
- ort – ONNX Runtime 的 Rust 绑定
- Lucide Icons – 开源图标库
- 感谢社区贡献者 @ukhack @duokebei 等提供的测试与反馈
chatless – 简洁易用的AI聊天应用
⭐ 如果这个项目对你有帮助,请给我们一个星标!
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