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nanobot
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nanobot

Active·★ 49.0k·MIT·Updated 2026-10-14
★ Most Popular★ Essential

nanobot, from the HKU Data Intelligence Lab (HKUDS), is an ultra-lightweight, self-hosted personal AI agent framework written in Python. It runs in a browser WebUI, in the terminal or inside chat apps, and combines tools, long-term memory, MCP integrations, model routing, subagents and scheduled automations around a deliberately small, readable core.

It suits individuals and small teams who want their own always-on assistant without adopting a large platform. Typical uses include chatting with an assistant from Telegram, Discord, Slack, WeChat, Feishu, email or Linear; running long-horizon goals and recurring tasks; and giving the agent tools such as file access, shell, web search, image generation and MCP servers. It works with OpenAI-compatible APIs and local models, offers fallbacks between providers, and exposes a Python SDK and an OpenAI-compatible API for integrations.

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Getting started: requires Python 3.11+. Run the one-command installer (or `pip install nanobot-ai`), then `nanobot webui` and choose a provider and model under Settings → Models. `nanobot gateway --background` keeps channels and automations running after you close the terminal.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool. Data as of 2026-10-10.

License
MIT
Latest release
v0.3.5 · 2026-09-15
Last commit
2026-10-10
Contributors
476
Forks
8,617
Open issues and PRs
817
First published
2026-02-01

Source: GitHub, npm and PyPI public APIs.

#AI Agent Framework#Self-hosted#Python#Multi-Agent#WebUI#Long-term Memory#Workflow Automation#LLM Integration
$ Install
$ curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh
↗ Visit site★ GitHub
01

Features

01Persistent workflows: goals, memory, tools, and chat context survive long-running work.
02Chat-native reach: WebUI, API, Telegram, Feishu, Slack, Discord, Teams, email, and Mattermost.
03Model freedom: OpenAI-compatible APIs, local LLMs, image generation, search, and fallbacks.
04Small core: readable internals with MCP, memory, deployment, and automation built in.
05Own your stack: inspect, customize, self-host, and extend without a giant platform.
02

Why choose it

+Small, readable core that is easy to inspect, customise and self-host.
+Reaches you through a WebUI, terminal and many chat apps, including Feishu, WeChat and Linear.
+Model freedom with OpenAI-compatible APIs, local models and provider fallbacks.
+Long-term memory, scheduled automations and subagents built in; MIT licensed.
03

Trade-offs

!Giving a personal agent shell and file access on your machine requires careful choice of workspace and access mode.
!The project moves quickly; the source install carries the newest features but is less stable than the PyPI release.
!As a lightweight framework it has fewer enterprise features (team management, audit, managed hosting) than larger platforms.
04

Compatibility

Python
Runtime
Verified via docs
MacOS
OS
Verified via docs
Linux
OS
Verified via docs
Windows
OS
Verified via docs
Docker
Deployment
Verified via docs
05

Quick start

1
$ curl -fsSL https://raw.githubusercontent.com/HKUDS/nanobot/main/scripts/install.sh | sh
06

Use cases

↳Running long-horizon goals and scheduled automations.
↳Connecting to various chat applications like Telegram, Discord, Slack for AI interaction.
↳Exposing a Python SDK and OpenAI-compatible API for custom integrations and development.
↳Deploying as a long-running local or server-side agent gateway.
07

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Stats
GitHub Stars★ 49.0k
Last commit1d ago
StatusActive
LicenseMIT
CategoryMulti-Agent
Trend (30d)
+1.9k↑ 4.8%
Links
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