nanobot: Ultra-Lightweight Personal AI Assistant

🐈 nanobot is an ultra-lightweight personal AI assistant inspired by OpenClaw

⚡️ Delivers core agent functionality in just ~4,000 lines of code — 99% smaller than Clawdbot's 430k+ lines.

📏 Real-time line count: 3,696 lines (run bash core_agent_lines.sh to verify anytime)

🖥️ Streamlit Web UI

nanobot now includes a full-featured Streamlit web interface for managing your AI assistant through a browser! This provides an intuitive graphical alternative to the CLI.

🚀 Quick Start

# Install Streamlit dependencies
pip install -r streamlit_requirements.txt

# Launch the UI (recommended)
python start_ui.py

# Or run directly with Streamlit
streamlit run streamlit_app/app.py

# On Windows, you can also use the batch file
run_streamlit.bat

The UI will be available at http://localhost:8501 by default.

✨ Features

The Streamlit UI provides a comprehensive dashboard with 13 feature-rich pages:

Page	Icon	Description
Setup	⚙️	Initial configuration wizard for API keys, model selection, and settings
Dashboard	📊	Overview of system status, metrics, and quick actions
Chat	💬	Interactive chat interface with the AI assistant
Providers	🤖	Manage LLM providers (OpenRouter, OpenAI, Anthropic, DeepSeek, etc.)
Channels	📱	Configure chat platforms (Telegram, Discord, WhatsApp, Slack, etc.)
Cron	⏰	Schedule automated tasks, reminders, and recurring jobs
Memory	🧠	View, search, and manage conversation memory
Skills	🎯	Browse, install, and enable agent skills
Sessions	💭	Manage conversation sessions and history
Tools	🔧	Configure built-in and custom tools
Workspace	📁	File browser and workspace management
Gateway	🌐	Start/stop the gateway for chat channels
Agent Tools	🛠️	Advanced tool configuration and management

🎨 UI Highlights

Modern Design: Clean, professional interface with intuitive navigation
Real-time Updates: Live status monitoring and metrics
Easy Configuration: Visual forms for all settings (no JSON editing required)
Full Chat Functionality: Complete chat interface with message history
Responsive Layout: Works on desktop and tablet screens
Dark/Light Themes: Supports Streamlit theme customization

📁 UI Structure

streamlit_app/
├── app.py              # Main application entry point
├── __init__.py         # Package initialization
└── pages/
    ├── 0_Setup.py      # Configuration wizard
    ├── 1_Dashboard.py  # Status overview
    ├── 2_Chat.py       # Chat interface
    ├── 3_Providers.py  # LLM provider management
    ├── 4_Channels.py   # Chat platform configuration
    ├── 5_Cron.py       # Scheduled tasks
    ├── 6_Memory.py     # Memory management
    ├── 7_Skills.py     # Skills browser
    ├── 8_Sessions.py   # Session management
    ├── 9_Tools.py      # Tool configuration
    ├── 10_Workspace.py # File browser
    ├── 11_Gateway.py   # Gateway controls
    └── 12_Agent_Tools.py # Advanced tools

🔧 Requirements

The Streamlit UI requires the following packages (included in streamlit_requirements.txt):

streamlit>=1.28.0
pandas>=2.0.0
plotly>=5.18.0

Tip

The UI connects to the same ~/.nanobot/config.json configuration used by the CLI. Changes made in the UI are immediately available to the CLI and vice versa.

📢 News

2026-02-16 🦞 nanobot now integrates a ClawHub skill — search and install public agent skills.
2026-02-15 🔑 nanobot now supports OpenAI Codex provider with OAuth login support.
2026-02-14 🔌 nanobot now supports MCP! See MCP section for details.
2026-02-13 🎉 Released v0.1.3.post7 — includes security hardening and multiple improvements. All users are recommended to upgrade to the latest version. See release notes for more details.
2026-02-12 🧠 Redesigned memory system — Less code, more reliable. Join the discussion about it!
2026-02-11 ✨ Enhanced CLI experience and added MiniMax support!
2026-02-10 🎉 Released v0.1.3.post6 with improvements! Check the updates notes and our roadmap.
2026-02-09 💬 Added Slack, Email, and QQ support — nanobot now supports multiple chat platforms!
2026-02-08 🔧 Refactored Providers—adding a new LLM provider now takes just 2 simple steps! Check here.
2026-02-07 🚀 Released v0.1.3.post5 with Qwen support & several key improvements! Check here for details.
2026-02-06 ✨ Added Moonshot/Kimi provider, Discord integration, and enhanced security hardening!
2026-02-05 ✨ Added Feishu channel, DeepSeek provider, and enhanced scheduled tasks support!
2026-02-04 🚀 Released v0.1.3.post4 with multi-provider & Docker support! Check here for details.
2026-02-03 ⚡ Integrated vLLM for local LLM support and improved natural language task scheduling!
2026-02-02 🎉 nanobot officially launched! Welcome to try 🐈 nanobot!

Key Features of nanobot:

🪶 Ultra-Lightweight: Just ~4,000 lines of core agent code — 99% smaller than Clawdbot.

🔬 Research-Ready: Clean, readable code that's easy to understand, modify, and extend for research.

⚡️ Lightning Fast: Minimal footprint means faster startup, lower resource usage, and quicker iterations.

💎 Easy-to-Use: One-click to deploy and you're ready to go.

🏗️ Architecture

✨ Features

📈 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

📦 Install

Install from source (latest features, recommended for development)

git clone https://github.com/HKUDS/nanobot.git
cd nanobot
pip install -e .

Install with uv (stable, fast)

uv tool install nanobot-ai

Install from PyPI (stable)

pip install nanobot-ai

🚀 Quick Start

Tip

Set your API key in ~/.nanobot/config.json. Get API keys: OpenRouter (Global) · Brave Search (optional, for web search)

1. Initialize

nanobot onboard

2. Configure (~/.nanobot/config.json)

Add or merge these two parts into your config (other options have defaults).

Set your API key (e.g. OpenRouter, recommended for global users):

{
  "providers": {
    "openrouter": {
      "apiKey": "sk-or-v1-xxx"
    }
  }
}

Set your model:

{
  "agents": {
    "defaults": {
      "model": "anthropic/claude-opus-4-5"
    }
  }
}

3. Chat

nanobot agent

That's it! You have a working AI assistant in 2 minutes.

💬 Chat Apps

Connect nanobot to your favorite chat platform.

Channel	What you need
Telegram	Bot token from @BotFather
Discord	Bot token + Message Content intent
WhatsApp	QR code scan
Feishu	App ID + App Secret
Mochat	Claw token (auto-setup available)
DingTalk	App Key + App Secret
Slack	Bot token + App-Level token
Email	IMAP/SMTP credentials
QQ	App ID + App Secret

Telegram (Recommended)

1. Create a bot

Open Telegram, search @BotFather
Send /newbot, follow prompts
Copy the token

2. Configure

{
  "channels": {
    "telegram": {
      "enabled": true,
      "token": "YOUR_BOT_TOKEN",
      "allowFrom": ["YOUR_USER_ID"]
    }
  }
}

You can find your User ID in Telegram settings. It is shown as @yourUserId. Copy this value without the @ symbol and paste it into the config file.

3. Run

nanobot gateway

Mochat (Claw IM)

Uses Socket.IO WebSocket by default, with HTTP polling fallback.

1. Ask nanobot to set up Mochat for you

Simply send this message to nanobot (replace xxx@xxx with your real email):

Read https://raw.githubusercontent.com/HKUDS/MoChat/refs/heads/main/skills/nanobot/skill.md and register on MoChat. My Email account is xxx@xxx Bind me as your owner and DM me on MoChat.

nanobot will automatically register, configure ~/.nanobot/config.json, and connect to Mochat.

2. Restart gateway

nanobot gateway

That's it — nanobot handles the rest!

Manual configuration (advanced)

If you prefer to configure manually, add the following to ~/.nanobot/config.json:

Keep claw_token private. It should only be sent in X-Claw-Token header to your Mochat API endpoint.

{
  "channels": {
    "mochat": {
      "enabled": true,
      "base_url": "https://mochat.io",
      "socket_url": "https://mochat.io",
      "socket_path": "/socket.io",
      "claw_token": "claw_xxx",
      "agent_user_id": "6982abcdef",
      "sessions": ["*"],
      "panels": ["*"],
      "reply_delay_mode": "non-mention",
      "reply_delay_ms": 120000
    }
  }
}

Discord

1. Create a bot

Go to https://discord.com/developers/applications
Create an application → Bot → Add Bot
Copy the bot token

2. Enable intents

In the Bot settings, enable MESSAGE CONTENT INTENT
(Optional) Enable SERVER MEMBERS INTENT if you plan to use allow lists based on member data

3. Get your User ID

Discord Settings → Advanced → enable Developer Mode
Right-click your avatar → Copy User ID

4. Configure

{
  "channels": {
    "discord": {
      "enabled": true,
      "token": "YOUR_BOT_TOKEN",
      "allowFrom": ["YOUR_USER_ID"]
    }
  }
}

5. Invite the bot

OAuth2 → URL Generator
Scopes: bot
Bot Permissions: Send Messages, Read Message History
Open the generated invite URL and add the bot to your server

6. Run

nanobot gateway

WhatsApp

Requires Node.js ≥18.

1. Link device

nanobot channels login
# Scan QR with WhatsApp → Settings → Linked Devices

2. Configure

{
  "channels": {
    "whatsapp": {
      "enabled": true,
      "allowFrom": ["+1234567890"]
    }
  }
}

3. Run (two terminals)

# Terminal 1
nanobot channels login

# Terminal 2
nanobot gateway

Feishu (飞书)

Uses WebSocket long connection — no public IP required.

1. Create a Feishu bot

Visit Feishu Open Platform
Create a new app → Enable Bot capability
Permissions: Add im:message (send messages)
Events: Add im.message.receive_v1 (receive messages)
- Select Long Connection mode (requires running nanobot first to establish connection)
Get App ID and App Secret from "Credentials & Basic Info"
Publish the app

2. Configure

{
  "channels": {
    "feishu": {
      "enabled": true,
      "appId": "cli_xxx",
      "appSecret": "xxx",
      "encryptKey": "",
      "verificationToken": "",
      "allowFrom": []
    }
  }
}

encryptKey and verificationToken are optional for Long Connection mode. allowFrom: Leave empty to allow all users, or add ["ou_xxx"] to restrict access.

3. Run

nanobot gateway

[!TIP] Feishu uses WebSocket to receive messages — no webhook or public IP needed!

QQ (QQ单聊)

Uses botpy SDK with WebSocket — no public IP required. Currently supports private messages only.

1. Register & create bot

Visit QQ Open Platform → Register as a developer (personal or enterprise)
Create a new bot application
Go to 开发设置 (Developer Settings) → copy AppID and AppSecret

2. Set up sandbox for testing

In the bot management console, find 沙箱配置 (Sandbox Config)
Under 在消息列表配置, click 添加成员 and add your own QQ number
Once added, scan the bot's QR code with mobile QQ → open the bot profile → tap "发消息" to start chatting

3. Configure

allowFrom: Leave empty for public access, or add user openids to restrict. You can find openids in the nanobot logs when a user messages the bot.

For production: submit a review in the bot console and publish. See QQ Bot Docs for the full publishing flow.

{
  "channels": {
    "qq": {
      "enabled": true,
      "appId": "YOUR_APP_ID",
      "secret": "YOUR_APP_SECRET",
      "allowFrom": []
    }
  }
}

4. Run

nanobot gateway

Now send a message to the bot from QQ — it should respond!

DingTalk (钉钉)

Uses Stream Mode — no public IP required.

1. Create a DingTalk bot

Visit DingTalk Open Platform
Create a new app -> Add Robot capability
Configuration:
- Toggle Stream Mode ON
Permissions: Add necessary permissions for sending messages
Get AppKey (Client ID) and AppSecret (Client Secret) from "Credentials"
Publish the app

2. Configure

{
  "channels": {
    "dingtalk": {
      "enabled": true,
      "clientId": "YOUR_APP_KEY",
      "clientSecret": "YOUR_APP_SECRET",
      "allowFrom": []
    }
  }
}

allowFrom: Leave empty to allow all users, or add ["staffId"] to restrict access.

3. Run

nanobot gateway

Slack

Uses Socket Mode — no public URL required.

1. Create a Slack app

Go to Slack API → Create New App → "From scratch"
Pick a name and select your workspace

2. Configure the app

Socket Mode: Toggle ON → Generate an App-Level Token with connections:write scope → copy it (xapp-...)
OAuth & Permissions: Add bot scopes: chat:write, reactions:write, app_mentions:read
Event Subscriptions: Toggle ON → Subscribe to bot events: message.im, message.channels, app_mention → Save Changes
App Home: Scroll to Show Tabs → Enable Messages Tab → Check "Allow users to send Slash commands and messages from the messages tab"
Install App: Click Install to Workspace → Authorize → copy the Bot Token (xoxb-...)

3. Configure nanobot

{
  "channels": {
    "slack": {
      "enabled": true,
      "botToken": "xoxb-...",
      "appToken": "xapp-...",
      "groupPolicy": "mention"
    }
  }
}

4. Run

nanobot gateway

DM the bot directly or @mention it in a channel — it should respond!

[!TIP]

groupPolicy: "mention" (default — respond only when @mentioned), "open" (respond to all channel messages), or "allowlist" (restrict to specific channels).

DM policy defaults to open. Set "dm": {"enabled": false} to disable DMs.

Email

Give nanobot its own email account. It polls IMAP for incoming mail and replies via SMTP — like a personal email assistant.

1. Get credentials (Gmail example)

Create a dedicated Gmail account for your bot (e.g. my-nanobot@gmail.com)
Enable 2-Step Verification → Create an App Password
Use this app password for both IMAP and SMTP

2. Configure

consentGranted must be true to allow mailbox access. This is a safety gate — set false to fully disable.

allowFrom: Leave empty to accept emails from anyone, or restrict to specific senders.

smtpUseTls and smtpUseSsl default to true / false respectively, which is correct for Gmail (port 587 + STARTTLS). No need to set them explicitly.

Set "autoReplyEnabled": false if you only want to read/analyze emails without sending automatic replies.

{
  "channels": {
    "email": {
      "enabled": true,
      "consentGranted": true,
      "imapHost": "imap.gmail.com",
      "imapPort": 993,
      "imapUsername": "my-nanobot@gmail.com",
      "imapPassword": "your-app-password",
      "smtpHost": "smtp.gmail.com",
      "smtpPort": 587,
      "smtpUsername": "my-nanobot@gmail.com",
      "smtpPassword": "your-app-password",
      "fromAddress": "my-nanobot@gmail.com",
      "allowFrom": ["your-real-email@gmail.com"]
    }
  }
}

3. Run

nanobot gateway

🌐 Agent Social Network

🐈 nanobot is capable of linking to the agent social network (agent community). Just send one message and your nanobot joins automatically!

Platform	How to Join (send this message to your bot)
Moltbook	`Read https://moltbook.com/skill.md and follow the instructions to join Moltbook`
ClawdChat	`Read https://clawdchat.ai/skill.md and follow the instructions to join ClawdChat`

Simply send the command above to your nanobot (via CLI or any chat channel), and it will handle the rest.

⚙️ Configuration

Config file: ~/.nanobot/config.json

Providers

Tip

Groq provides free voice transcription via Whisper. If configured, Telegram voice messages will be automatically transcribed.
Zhipu Coding Plan: If you're on Zhipu's coding plan, set "apiBase": "https://open.bigmodel.cn/api/coding/paas/v4" in your zhipu provider config.
MiniMax (Mainland China): If your API key is from MiniMax's mainland China platform (minimaxi.com), set "apiBase": "https://api.minimaxi.com/v1" in your minimax provider config.

Provider	Purpose	Get API Key
`custom`	Any OpenAI-compatible endpoint	—
`openrouter`	LLM (recommended, access to all models)	openrouter.ai
`anthropic`	LLM (Claude direct)	console.anthropic.com
`openai`	LLM (GPT direct)	platform.openai.com
`deepseek`	LLM (DeepSeek direct)	platform.deepseek.com
`groq`	LLM + Voice transcription (Whisper)	console.groq.com
`gemini`	LLM (Gemini direct)	aistudio.google.com
`minimax`	LLM (MiniMax direct)	platform.minimax.io
`aihubmix`	LLM (API gateway, access to all models)	aihubmix.com
`dashscope`	LLM (Qwen)	dashscope.console.aliyun.com
`moonshot`	LLM (Moonshot/Kimi)	platform.moonshot.cn
`zhipu`	LLM (Zhipu GLM)	open.bigmodel.cn
`vllm`	LLM (local, any OpenAI-compatible server)	—
`openai_codex`	LLM (Codex, OAuth)	`nanobot provider login openai-codex`
`github_copilot`	LLM (GitHub Copilot, OAuth)	Requires GitHub Copilot subscription

OpenAI Codex (OAuth)

Codex uses OAuth instead of API keys. Requires a ChatGPT Plus or Pro account.

1. Login:

nanobot provider login openai-codex

2. Set model (merge into ~/.nanobot/config.json):

{
  "agents": {
    "defaults": {
      "model": "openai-codex/gpt-5.1-codex"
    }
  }
}

3. Chat:

nanobot agent -m "Hello!"

Docker users: use docker run -it for interactive OAuth login.

Custom Provider (Any OpenAI-compatible API)

If your provider is not listed above but exposes an OpenAI-compatible API (e.g. Together AI, Fireworks, Azure OpenAI, self-hosted endpoints), use the custom provider:

{
  "providers": {
    "custom": {
      "apiKey": "your-api-key",
      "apiBase": "https://api.your-provider.com/v1"
    }
  },
  "agents": {
    "defaults": {
      "model": "your-model-name"
    }
  }
}

The custom provider routes through LiteLLM's OpenAI-compatible path. It works with any endpoint that follows the OpenAI chat completions API format. The model name is passed directly to the endpoint without any prefix.

vLLM (local / OpenAI-compatible)

Run your own model with vLLM or any OpenAI-compatible server, then add to config:

1. Start the server (example):

vllm serve meta-llama/Llama-3.1-8B-Instruct --port 8000

2. Add to config (partial — merge into ~/.nanobot/config.json):

Provider (key can be any non-empty string for local):

{
  "providers": {
    "vllm": {
      "apiKey": "dummy",
      "apiBase": "http://localhost:8000/v1"
    }
  }
}

Model:

{
  "agents": {
    "defaults": {
      "model": "meta-llama/Llama-3.1-8B-Instruct"
    }
  }
}

Adding a New Provider (Developer Guide)

nanobot uses a Provider Registry (nanobot/providers/registry.py) as the single source of truth. Adding a new provider only takes 2 steps — no if-elif chains to touch.

Step 1. Add a ProviderSpec entry to PROVIDERS in nanobot/providers/registry.py:

ProviderSpec(
    name="myprovider",                   # config field name
    keywords=("myprovider", "mymodel"),  # model-name keywords for auto-matching
    env_key="MYPROVIDER_API_KEY",        # env var for LiteLLM
    display_name="My Provider",          # shown in `nanobot status`
    litellm_prefix="myprovider",         # auto-prefix: model → myprovider/model
    skip_prefixes=("myprovider/",),      # don't double-prefix
)

Step 2. Add a field to ProvidersConfig in nanobot/config/schema.py:

class ProvidersConfig(BaseModel):
    ...
    myprovider: ProviderConfig = ProviderConfig()

That's it! Environment variables, model prefixing, config matching, and nanobot status display will all work automatically.

Common ProviderSpec options:

Field	Description	Example
`litellm_prefix`	Auto-prefix model names for LiteLLM	`"dashscope"` → `dashscope/qwen-max`
`skip_prefixes`	Don't prefix if model already starts with these	`("dashscope/", "openrouter/")`
`env_extras`	Additional env vars to set	`(("ZHIPUAI_API_KEY", "{api_key}"),)`
`model_overrides`	Per-model parameter overrides	`(("kimi-k2.5", {"temperature": 1.0}),)`
`is_gateway`	Can route any model (like OpenRouter)	`True`
`detect_by_key_prefix`	Detect gateway by API key prefix	`"sk-or-"`
`detect_by_base_keyword`	Detect gateway by API base URL	`"openrouter"`
`strip_model_prefix`	Strip existing prefix before re-prefixing	`True` (for AiHubMix)

MCP (Model Context Protocol)

Tip

The config format is compatible with Claude Desktop / Cursor. You can copy MCP server configs directly from any MCP server's README.

nanobot supports MCP — connect external tool servers and use them as native agent tools.

Add MCP servers to your config.json:

{
  "tools": {
    "mcpServers": {
      "filesystem": {
        "command": "npx",
        "args": ["-y", "@modelcontextprotocol/server-filesystem", "/path/to/dir"]
      }
    }
  }
}

Two transport modes are supported:

Mode	Config	Example
Stdio	`command` + `args`	Local process via `npx` / `uvx`
HTTP	`url`	Remote endpoint (`https://mcp.example.com/sse`)

MCP tools are automatically discovered and registered on startup. The LLM can use them alongside built-in tools — no extra configuration needed.

Security

Tip

For production deployments, set "restrictToWorkspace": true in your config to sandbox the agent.

Option	Default	Description
`tools.restrictToWorkspace`	`false`	When `true`, restricts all agent tools (shell, file read/write/edit, list) to the workspace directory. Prevents path traversal and out-of-scope access.
`channels.*.allowFrom`	`[]` (allow all)	Whitelist of user IDs. Empty = allow everyone; non-empty = only listed users can interact.

CLI Reference

Command	Description
`nanobot onboard`	Initialize config & workspace
`nanobot agent -m "..."`	Chat with the agent
`nanobot agent`	Interactive chat mode
`nanobot agent --no-markdown`	Show plain-text replies
`nanobot agent --logs`	Show runtime logs during chat
`nanobot gateway`	Start the gateway
`nanobot status`	Show status
`nanobot provider login openai-codex`	OAuth login for providers
`nanobot channels login`	Link WhatsApp (scan QR)
`nanobot channels status`	Show channel status

Interactive mode exits: exit, quit, /exit, /quit, :q, or Ctrl+D.

Scheduled Tasks (Cron)

# Add a job
nanobot cron add --name "daily" --message "Good morning!" --cron "0 9 * * *"
nanobot cron add --name "hourly" --message "Check status" --every 3600

# List jobs
nanobot cron list

# Remove a job
nanobot cron remove <job_id>

🐳 Docker

Tip

The -v ~/.nanobot:/root/.nanobot flag mounts your local config directory into the container, so your config and workspace persist across container restarts.

Docker Compose

docker compose run --rm nanobot-cli onboard   # first-time setup
vim ~/.nanobot/config.json                     # add API keys
docker compose up -d nanobot-gateway           # start gateway

docker compose run --rm nanobot-cli agent -m "Hello!"   # run CLI
docker compose logs -f nanobot-gateway                   # view logs
docker compose down                                      # stop

Docker

# Build the image
docker build -t nanobot .

# Initialize config (first time only)
docker run -v ~/.nanobot:/root/.nanobot --rm nanobot onboard

# Edit config on host to add API keys
vim ~/.nanobot/config.json

# Run gateway (connects to enabled channels, e.g. Telegram/Discord/Mochat)
docker run -v ~/.nanobot:/root/.nanobot -p 18790:18790 nanobot gateway

# Or run a single command
docker run -v ~/.nanobot:/root/.nanobot --rm nanobot agent -m "Hello!"
docker run -v ~/.nanobot:/root/.nanobot --rm nanobot status

📁 Project Structure

nanobot/
├── agent/          # 🧠 Core agent logic
│   ├── loop.py     #    Agent loop (LLM ↔ tool execution)
│   ├── context.py  #    Prompt builder
│   ├── memory.py   #    Persistent memory
│   ├── skills.py   #    Skills loader
│   ├── subagent.py #    Background task execution
│   └── tools/      #    Built-in tools (incl. spawn)
├── skills/         # 🎯 Bundled skills (github, weather, tmux...)
├── channels/       # 📱 Chat channel integrations
├── bus/            # 🚌 Message routing
├── cron/           # ⏰ Scheduled tasks
├── ├── heartbeat/  # 💓 Proactive wake-up
├── providers/      # 🤖 LLM providers (OpenRouter, etc.)
├── session/        # 💬 Conversation sessions
├── config/         # ⚙️ Configuration
├── cli/            # 🖥️ Commands
└── streamlit_app/  # 🌐 Streamlit Web UI
    ├── app.py      #    Main application entry
    └── pages/      #    UI pages (Dashboard, Chat, etc.)

🤝 Contribute & Roadmap

PRs welcome! The codebase is intentionally small and readable. 🤗

Roadmap — Pick an item and open a PR!

Multi-modal — See and hear (images, voice, video)
Long-term memory — Never forget important context
Better reasoning — Multi-step planning and reflection
More integrations — Calendar and more
Self-improvement — Learn from feedback and mistakes

Contributors

⭐ Star History

Thanks for visiting ✨ nanobot!

_{nanobot is for educational, research, and technical exchange purposes only}

Name		Name	Last commit message	Last commit date
Latest commit History 417 Commits
bridge		bridge
case		case
nanobot		nanobot
streamlit_app		streamlit_app
tests		tests
workspace		workspace
.dockerignore		.dockerignore
.gitignore		.gitignore
COMMUNICATION.md		COMMUNICATION.md
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
SECURITY.md		SECURITY.md
STREAMLIT_UI_README.md		STREAMLIT_UI_README.md
core_agent_lines.sh		core_agent_lines.sh
docker-compose.yml		docker-compose.yml
nanobot_arch.png		nanobot_arch.png
nanobot_logo.png		nanobot_logo.png
pyproject.toml		pyproject.toml
run_streamlit.bat		run_streamlit.bat
start_ui.py		start_ui.py
streamlit_requirements.txt		streamlit_requirements.txt

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nanobot: Ultra-Lightweight Personal AI Assistant

🖥️ Streamlit Web UI

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nanobot: Ultra-Lightweight Personal AI Assistant

🖥️ Streamlit Web UI

🚀 Quick Start

✨ Features

🎨 UI Highlights

📁 UI Structure

🔧 Requirements

📢 News

Key Features of nanobot:

🏗️ Architecture

✨ Features

📦 Install

🚀 Quick Start

💬 Chat Apps

🌐 Agent Social Network

⚙️ Configuration

Providers

MCP (Model Context Protocol)

Security

CLI Reference

🐳 Docker

Docker Compose

Docker

📁 Project Structure

🤝 Contribute & Roadmap

Contributors

⭐ Star History

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