Nanobot — AI Agent Framework: Live Stats & TrendScore

Live GitHub stats, community sentiment, and trend data for Nanobot. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Jun 19, 2026 • Sentiment updated: Jun 24, 2026

GitHub Statistics

Community Sentiment

Community Buzz: People are convinced you have to use doubles because of the inaccuracy of floats, as mentioned on HackerNews

Pros & Cons

What People Love

Innovative approach, Reddit users praise the potential of nanobots

Common Complaints

Limited documentation, Difficulty with integration

Biggest Positive: Innovative tech

Biggest Negative: No robust testing

Why Nanobot Stands Out

nanobot is different from other AI agent frameworks because of its ultra-lightweight architecture, which delivers core agent functionality with 99% fewer lines of code. This makes it ideal for resource-constrained devices and allows developers to create agents that can run on a wide range of hardware. Additionally, nanobot's support for multiple providers and channels enables developers to create agents that can interact with users through various channels, making it a valuable tool for building multimodal AI agents. The project's focus on reliability and security also sets it apart from other frameworks, with features such as core runtime hardening and token-based memory.

Built With

Build a personal AI assistant that integrates with WeChat and Discord — nanobot's ultra-lightweight architecture delivers core agent functionality with 99% fewer lines of code, making it ideal for resource-constrained devices, Build a multimodal AI agent that handles voice, text, and media interactions — nanobot's support for WeChat, Telegram, and Feishu enables developers to create agents that can interact with users through various channels, Build a real-time AI agent that can handle long-running tasks — nanobot's core runtime hardening and improved reliability features ensure that agents can run tasks without interruptions, Build a customizable AI agent that can be tailored to specific use cases — nanobot's provider-agnostic architecture and support for multiple providers allow developers to create agents that can work with different services, Build a secure AI agent that can handle sensitive user data — nanobot's token-based memory and safer default access control features ensure that user data is protected

Getting Started

  1. Install nanobot using pip: `pip install nanobot-ai`
  2. Configure nanobot to use a specific provider, such as OpenAI or Anthropic, by running `nanobot-config --provider <provider>`
  3. Set up a new agent by running `nanobot-create-agent --name <agent_name>`
  4. Configure the agent to use a specific channel, such as WeChat or Discord, by running `nanobot-config --channel <channel>`
  5. Try interacting with the agent using the `nanobot-interact` command to verify that it works

About

Lightweight, open-source AI agent for your tools, chats, and workflows.

Official site: https://nanobot.wiki

Category & Tags

Category: development

Tags: ai, ai-agent, ai-agents, anthropic, chatgpt, claude, claude-code, codex, codex-cli, llm, nanobot, openai, openclaw

Market Context

Competitive with other AI solutions