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nanobot: 3-day Study Repository

🇨🇳 中文文档 (Chinese)

🐈 nanobot is an ultra-lightweight personal AI assistant designed to be learned, dissected, and mastered.

Unlike bloated frameworks that hide their logic, nanobot delivers core agent functionality in just ~3,500 lines of code. It's the perfect "textbook" implementation of a modern LLM agent.

💡 Basic Idea

An AI Agent is not just a chatbot. It is a system that can:

1. Perceive: Read files, search the web, see the terminal output.
2. Think: Use an LLM (Large Language Model) to reason about what to do next.
3. Act: Execute tools (Shell, File I/O, API calls) to affect the environment.
4. Loop: Observe the result of its action and decide the next step.

nanobot implements this Perceive-Think-Act-Loop in its purest form in agent/loop.py. By studying this repository, you aren't just learning a tool; you are learning the fundamental anatomy of Agentic AI.

Tip

Using an AI Coding Assistant? (Cursor, Claude Code, GitHub Copilot)

You can turn your AI assistant into a Personal Nanobot Tutor!

1. Open AI_COPILOT.md.
2. Copy its content or ask your AI to "Read AI_COPILOT.md and act as my tutor".
3. The AI will now guide you through the 3-Day Plan using the Socratic method, helping you understand the code instead of just writing it for you.

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📅 3-Day Mastery Plan

Follow this guided path to go from "User" to "AI Engineer" in just one weekend (2-3 hours/day).

Day 1: The Soul (Architecture)

Objective: Understand how an LLM becomes an Agent.

1. Read (30 min):
   • agent/loop.py: This is the heart. Read how _process_message handles the LLM -> Tool -> LLM cycle.
   • config/: See how we manage prompts and model settings.
2. Action (1 hour):
   • Run nanobot onboard to initialize.
   • Chat: nanobot agent -m "Calculate 128 * 455".
   • Trace: Open ~/.nanobot/workspace and find the log file. Follow the execution path you just read in loop.py.
3. Challenge (1 hour):
   • Modify agent/prompts.py (or equivalent) to give the bot a "Pirate" personality.
   • Restart and verify: nanobot agent -m "Who are you?".

Day 2: The Hands (Skills & Tools)

Objective: Teach the AI to interact with the real world.

1. Read (30 min):
   • agent/tools/: Look at web.py to see how we define tools.
   • skills/: Understand how to bundle tools into skills.
2. Action (1 hour):
   • Create a simple python script my_tool.py that prints "Hello from tool!".
   • Register it in the agent configuration.
3. Challenge (1.5 hours):
   • Build a "Daily Briefing" Skill:
     • Write a tool that fetches top Hacker News headlines (use an API or scraping).
     • Combine it with the existing weather tool.
     • Ask nanobot: "Give me my daily briefing."

Day 3: The Body (Deployment & Channels)

Objective: Run your agent 24/7.

1. Read (30 min):
   • channels/: How we bridge to Telegram/WhatsApp.
   • cron/: How the agent wakes itself up.
2. Action (1 hour):
   • Set up a mock Telegram bot (or real one via @BotFather).
   • Configure cron to run your "Daily Briefing" skill every morning at 8:00 AM.
3. Challenge (1.5 hours):
   • Dockerize: Build the container using the provided Dockerfile.
   • Run it independently of your terminal.
   • Chat with it via Telegram while it runs in Docker.

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📦 Setup for Study

This repository contains the Study Plan and Tutor Instructions. To follow the plan, you need the actual nanobot source code.

1. Clone the Repository (Recursive)

This command downloads both the study guide AND the nanobot source code at once.

git clone --recursive https://github.com/YOUR_USERNAME/nanobot-study.git
cd nanobot-study

2. Install Dependencies

pip install -e nanobot/

3. Start Learning

Return to this README (or AI_COPILOT.md) and begin your 3-Day Mastery Plan tasks. Note that the source code is now in the nanobot/ subdirectory.

🤖 How to Learn with an AI Tutor

If you are using Cursor, Claude Code, or GitHub Copilot, paste the content of AI_COPILOT.md into your chat. The AI will then act as a Socratic Tutor.

Example Interaction:

You: "How does the agent decide which tool to use?"

Standard AI: "It uses the _process_message function in loop.py. Here is the code..." (Gives you the answer, you learn nothing)

Nanobot Tutor (Socratic): "That's the core of the agent! Open nanobot/agent/loop.py and look at the _process_message method. Can you spot where we call self.llm.chat? What argument are we passing to it that contains the tool definitions?"

Your Goal: Don't just copy code. Answer the Tutor's questions to build your mental model of the system.

🚀 Quick Start

1. Initialize: nanobot onboard
2. Configure: Edit ~/.nanobot/config.json with your API keys (OpenRouter/OpenAI/Anthropic).
3. Chat: nanobot agent -m "Hello World"

🏗️ Architecture Reference

• bridge/: Connectivity to external worlds (Telegram, etc).
• agent/: The cognitive core.
• memory/: Long-term storage (your workspace/).

🔗 Related Projects

• HKUDS/nanobot - The original lightweight agent framework this study guide is based on.
• OpenClaw - A powerful autonomous agent framework for complex tasks.

📚 References

• ReAct: Synergizing Reasoning and Acting in Language Models - Generally considered the seminal paper for modern Agents.
• AutoGPT - An early popular implementation of autonomous agents.
• LangChain - A framework for developing applications powered by language models.

🤝 Contribute

We love PRs! If you finish your "Day 3 Challenge" and make a cool skill, make a PR to add it to the skills/ directory.

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_{Special thanks to the original HKUDS/nanobot repository for the excellent base implementation.
nanobot is for educational, research, and technical exchange purposes only}