经 AI Skill Hub 精选评估,纳米机器人AI助手 获评「强烈推荐」。在 GitHub 上收获超过 42.3k 颗 Star,这款AI工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.2 分,适合有一定技术背景的用户使用。
超轻量级开源个人AI智能体框架,支持多大模型集成(Claude、ChatGPT等),提供工作流编排和自动化能力。适合开发者、产品经理快速构建AI助手原型和自动化任务。
纳米机器人AI助手 是一款基于 Python 开发的开源工具,专注于 AI智能体、工作流自动化、多模型集成 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
超轻量级开源个人AI智能体框架,支持多大模型集成(Claude、ChatGPT等),提供工作流编排和自动化能力。适合开发者、产品经理快速构建AI助手原型和自动化任务。
纳米机器人AI助手 是一款基于 Python 开发的开源工具,专注于 AI智能体、工作流自动化、多模型集成 等核心功能。作为 GitHub 开源项目,它拥有活跃的社区支持和持续的版本迭代,代码完全透明可审计,支持本地部署以保护数据隐私。无论是个人使用还是集成到企业工作流,都能提供稳定可靠的解决方案。
# 方式一:pip 安装(推荐)
pip install nanobot
# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install nanobot
# 方式三:从源码安装(获取最新功能)
git clone https://github.com/HKUDS/nanobot
cd nanobot
pip install -e .
# 验证安装
python -c "import nanobot; print('安装成功')"
# 命令行使用
nanobot --help
# 基本用法
nanobot input_file -o output_file
# Python 代码中调用
import nanobot
# 示例
result = nanobot.process("input")
print(result)
# nanobot 配置文件示例(config.yml) app: name: "nanobot" debug: false log_level: "INFO" # 运行时指定配置文件 nanobot --config config.yml # 或通过环境变量配置 export NANOBOT_API_KEY="your-key" export NANOBOT_OUTPUT_DIR="./output"
<picture> <source media="(prefers-color-scheme: dark)" srcset="./images/readme-cover-dark.png"> <img alt="nanobot README cover" src="./images/readme-cover-light.png"> </picture>
English | 简体中文 | 繁體中文 | Español | Français | Bahasa Indonesia | 日本語 | 한국어 | Русский | Tiếng Việt
🐈 nanobot is an open-source, ultra-lightweight personal AI agent you can truly own. It keeps the agent core small and readable while giving you the practical pieces for real long-running work: WebUI, chat channels, tools, memory, MCP, model routing, automation, and deployment.
📈 24/7 Real-Time Market Analysis |
🚀 Full-Stack Software Engineer |
📅 Smart Daily Routine Manager |
📚 Personal Knowledge Assistant |
|---|---|---|---|
|
|
|
|
| Discovery • Insights • Trends | Develop • Deploy • Scale | Schedule • Automate • Organize | Learn • Memory • Reasoning |
[!IMPORTANT] If you want the newest features and experiments, install from source. If you want the most stable day-to-day experience, install from PyPI or with uv.
Pick one install method:
Prerequisites: Python 3.11 or newer. Git is only needed for a source install; Node.js/Bun are only needed if you are developing the WebUI itself.
If terminals, API keys, or config files are new to you, use the guided zero-background walkthrough in Start Without Technical Background instead of this compact README path.
One-command setup
macOS / Linux:
curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh
Windows PowerShell:
irm https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.ps1 | iex
The default command installs or upgrades nanobot-ai from PyPI, then starts nanobot onboard --wizard. It avoids system-wide pip installs by using an active virtual environment, uv, pipx, or a managed venv under ~/.nanobot/venv. If Quick Start finishes and you enabled the WebSocket channel, skip the manual initialize/configure steps below and go straight to Open the WebUI.
To preview the plan without changing your environment, pass --dry-run; combine it with --dev when you want to preview the main-branch install.
curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh -s -- --dry-run
& ([scriptblock]::Create((irm https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.ps1))) --dry-run
To install the current main branch instead, pass --dev:
curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh -s -- --dev
& ([scriptblock]::Create((irm https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.ps1))) --dev
If you prefer to inspect the script first, open scripts/install.sh or scripts/install.ps1.
Install with uv
uv tool install nanobot-ai
Install from PyPI with pip
python -m pip install nanobot-ai
If pip reports externally-managed-environment on macOS or Linux, use the one-command installer, uv tool install nanobot-ai, pipx install nanobot-ai, or install inside a virtual environment.
Install from source
git clone https://github.com/HKUDS/nanobot.git
cd nanobot
python -m pip install -e .
Verify the install:
nanobot --version
1. Initialize
Skip this step if the one-command setup already started the wizard and Quick Start finished there.
nanobot onboard
Use nanobot onboard --wizard if you prefer an interactive setup.
2. Configure (~/.nanobot/config.json)
Skip this step if you already configured provider and model settings in the wizard.
nanobot onboard creates ~/.nanobot/config.json and ~/.nanobot/workspace/. Configure these two parts in the config file. Add or merge the following blocks into the existing file instead of replacing the whole file.
The example below uses a generic OpenAI-compatible custom provider so the compact path does not recommend one hosted service. Provider examples are recipes, not rankings or endorsements. For copyable provider-specific setup, see Provider Cookbook.
Set your API key:
{
"providers": {
"custom": {
"apiKey": "your-api-key",
"apiBase": "https://api.example.com/v1"
}
}
}
Set a model preset and make it active:
{
"modelPresets": {
"primary": {
"label": "Primary",
"provider": "custom",
"model": "model-id-from-your-provider",
"maxTokens": 8192,
"contextWindowTokens": 200000,
"temperature": 0.1
}
},
"agents": {
"defaults": {
"modelPreset": "primary"
}
}
}
Direct agents.defaults.provider and agents.defaults.model still work for existing configs, but named presets are the recommended path because they also power /model switching and fallbackModels.
For another provider, the same config shape still applies:
| Replace | Where |
|---|---|
| Provider config key | providers.<provider> |
| API key | providers.<provider>.apiKey |
| Preset provider name | modelPresets.primary.provider |
| Model ID | modelPresets.primary.model |
| Endpoint URL, only when needed | providers.<provider>.apiBase |
3. Open the WebUI
If Quick Start enabled the WebSocket channel, start the gateway:
nanobot gateway
Leave that terminal open, then open http://127.0.0.1:8765 in your browser. Enter the WebUI password you set in the wizard, then send your first message there. Prefer not to keep a terminal open? Use nanobot gateway --background, then manage it with nanobot gateway status, logs, restart, and stop.
For manual or terminal-only setup, test one CLI message:
nanobot status
nanobot agent -m "Hello!"
In nanobot status, it is normal for most providers to say not set. The active preset's provider should be configured, and Config plus Workspace should show check marks.
If that works, start an interactive chat:
nanobot agent
Need help with PATH, API keys, provider/model matching, or JSON errors? See the fuller Install and Quick Start and Troubleshooting.
设计精简高效,42k星标证明社区认可。Python实现易集成,多模型支持灵活性强,是构建个人AI工具的优选方案。
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。
AI Skill Hub 点评:纳米机器人AI助手 的核心功能完整,质量优秀。对于AI爱好者来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | nanobot |
| 原始描述 | 开源AI工作流:"🐈 nanobot: The Ultra-Lightweight Personal AI Agent"。⭐42.3k · Python |
| Topics | AI智能体工作流自动化多模型集成轻量级框架 |
| GitHub | https://github.com/HKUDS/nanobot |
| License | MIT |
| 语言 | Python |
收录时间:2026-05-13 · 更新时间:2026-05-16 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。