HKUDS-nanobot/docs/concepts.md

Concepts

Use this page when you want to understand nanobot before changing advanced settings. It explains the moving parts without requiring you to read the source first.

If you want source-file ownership and extension points, read architecture.md after this page.

Runtime Shape

nanobot has one small core loop and several ways to enter it:

Part	What it does
Agent loop	Builds context, selects the session, calls the provider, runs tools, and publishes replies
Providers	LLM backends such as OpenRouter, Anthropic, OpenAI, Bedrock, Ollama, vLLM, and other OpenAI-compatible APIs
Channels	User-facing transports such as CLI, WebUI/WebSocket, Telegram, Discord, Slack, Feishu, WeChat, Email, and others
Tools	Capabilities the model may call, including files, shell, web search/fetch, MCP, cron, image generation, and subagents
Memory	Workspace files and session history that keep useful context across turns
Gateway	Long-running process that connects enabled channels and serves the health endpoint

The simplest path is nanobot agent -m "Hello!": one inbound message goes through the agent loop and prints the reply in your terminal. The long-running path is nanobot gateway: channels receive messages from chat apps or the WebUI, publish them to the same agent loop, and send replies back to the originating channel.

Config vs Workspace

The default instance lives under ~/.nanobot/:

Path	Meaning
~/.nanobot/config.json	Instance configuration: providers, model defaults, channels, tools, gateway, API, and runtime options
~/.nanobot/workspace/	Agent workspace: memory, sessions, heartbeat tasks, cron jobs, skills, and generated artifacts

You can override both with command flags:

nanobot onboard --config ./bot-a/config.json --workspace ./bot-a/workspace
nanobot agent --config ./bot-a/config.json --workspace ./bot-a/workspace -m "Hello"
nanobot gateway --config ./bot-a/config.json --workspace ./bot-a/workspace

The config file controls what nanobot may use. The workspace is where nanobot keeps state for that instance.

Config Format

config.json accepts both camelCase and snake_case keys. The docs use camelCase because nanobot writes config back to disk with camelCase aliases, for example apiKey, modelPresets, intervalS, and maxToolResultChars.

Most examples are partial snippets. Merge them into the existing file created by nanobot onboard; do not replace the whole file unless you want to reset the instance.

One Agent Turn

A normal turn follows this flow:

1. A channel receives a user message and publishes it to the message bus.
2. The agent loop chooses a session key and builds context from the workspace, skills, memory, recent messages, channel metadata, and runtime settings.
3. The provider receives the model request.
4. If the model asks for tools, the runner executes them and feeds results back to the model.
5. The final reply is saved to the session and sent back through the channel.

That flow is the same whether the message starts in the CLI, WebUI, Telegram, Discord, or another channel.

CLI, Gateway, API, and WebUI

Entry point	Command	Use it for
CLI one-shot	nanobot agent -m "..."	First-run checks, scripts, and quick local questions
CLI interactive	nanobot agent	Terminal chat with persistent session history
Gateway	nanobot gateway	Chat apps, WebUI, heartbeat, Dream, and long-running service mode
OpenAI-compatible API	nanobot serve	Programmatic access through /v1/chat/completions
WebUI	nanobot gateway plus WebSocket channel	Browser workbench served by the WebSocket channel on port 8765

The gateway health endpoint is on gateway.port (18790 by default). The browser WebUI is served by the WebSocket channel (8765 by default), not by the health endpoint.

Provider and Model Selection

The active model should normally come from a named modelPresets entry selected by agents.defaults.modelPreset. Direct agents.defaults.provider and agents.defaults.model still form the implicit default preset for older or minimal configs. The active provider is resolved in this order:

1. If the active preset provider or implicit default provider is not "auto", nanobot uses that provider.
2. If provider is "auto", nanobot tries to infer the provider from the model name, configured API keys, local provider base URLs, or gateway providers.
3. OAuth providers such as OpenAI Codex and GitHub Copilot require explicit login and explicit provider/model selection inside the active preset.

Pin the provider inside the preset when setting up for the first time. It is easier to debug:

{
  "modelPresets": {
    "primary": {
      "provider": "openrouter",
      "model": "anthropic/claude-opus-4.5"
    }
  },
  "agents": {
    "defaults": {
      "modelPreset": "primary"
    }
  }
}

See providers.md for practical examples and configuration.md#providers for the full provider reference.

Channels and Sessions

Each channel maps inbound messages to a session key. That lets independent conversations keep separate history. The WebUI also supports multiple chats and workspace-scoped metadata for project workspaces.

agents.defaults.unifiedSession can intentionally share one session across channels for a single-user multi-device setup. Leave it off if you expect separate people, groups, channels, or projects to keep separate context.

Memory, Sessions, and Dream

nanobot uses two related stores:

Store	Location	Purpose
Sessions	<workspace>/sessions/*.jsonl	Recent conversation turns replayed into context
Memory	<workspace>/memory/MEMORY.md and <workspace>/memory/history.jsonl	Long-term facts and consolidated history

Dream is a periodic consolidation job. It reads accumulated history and updates workspace memory so useful context can survive beyond short session replay.

See memory.md for the detailed design.

Tools and Safety

Tools are discovered automatically from built-in modules and plugin entry points. Common tool groups include:

• file read/write/edit and patching;
• shell execution with configurable sandboxing;
• web search and web fetch with SSRF checks;
• MCP servers;
• cron reminders, local triggers, and heartbeat tasks;
• image generation;
• subagents and runtime self-inspection.

Security-sensitive controls live in configuration.md#security. For production or shared chat apps, also configure channel access controls such as allowFrom, pairing, or WebSocket tokens.

Background Jobs

When nanobot gateway starts, it runs workspace-scoped automations and registers system jobs:

• dream, when agents.defaults.dream.enabled is true;
• heartbeat, when gateway.heartbeat.enabled is true.

Heartbeat reads <workspace>/HEARTBEAT.md. If the file has tasks under ## Active Tasks, nanobot executes them and sends only useful/actionable results to the most recently active chat target. Routine "nothing changed" results are suppressed.

User-created reminders use the same cron service but are not the same as the protected heartbeat system job. They run as scheduled turns in their origin chat/session and normally deliver the result back to that channel.

Local triggers are also session-bound, but they do not have their own schedule. Create one from the target chat with /trigger <name>, then call nanobot trigger <id> "<message>" when a local script or external service wants nanobot to respond in that session. Webhook servers, third-party auth, and event-to-message formatting stay outside nanobot. Trigger deliveries are stored in the workspace until the linked agent turn finishes successfully. If the target session is busy, the trigger waits until that session is idle instead of being injected into the active turn. The message is recorded as an automation turn in that session. Delivery is at-least-once, so external systems should tolerate repeated trigger messages; a delivery that reaches the agent but fails is marked failed rather than retried forever.

Where to Go Next

Need	Read
First working install	quick-start.md
Provider/model setup	providers.md
Chat app setup	chat-apps.md
Complete config reference	configuration.md
Runtime debugging	troubleshooting.md