macchiato-bot 0.2.3

macchiatoBot — daemon-first, tool-driven LLM assistant with remote worker CLI

macchiatoBot

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macchiatoBot is a daemon-first, tool-driven LLM assistant. The daemon owns sessions, scheduling, IPC, tool execution, permissions, memory, and frontend integration; CLI, Feishu, MCP, and automation jobs all enter through that shared runtime.

The repository currently publishes two installable surfaces:

Package	Role	Commands
macchiato-bot	Full assistant runtime for cloud/dev/local bot use	macchiato, macchiato-daemon, macchiato-remote
macchiato-remote	Lightweight worker for exposing one authorized local workspace to a bot daemon	macchiato-remote

In a checkout, the root main.py and automation_daemon.py files are thin compatibility shims around the packaged entrypoints.

Runtime Shape

CLI / Feishu / MCP / automation trigger
        |
        v
Automation IPC + Core Gateway + task queue
        |
        v
KernelScheduler + CorePool
        |
        v
AgentKernel
  - tool execution
  - permission checks
  - path and remote-workspace routing
  - context compression
        |
        v
AgentCore
  - prompt assembly
  - LLM provider routing
  - memory recall
  - tool-calling loop

Short version: AgentCore thinks, AgentKernel executes, and the automation daemon keeps the long-running process, sessions, queue, and IPC stable.

Architecture Principles

• Daemon-first runtime: long-running state belongs to macchiato-daemon / automation_daemon.py, not to individual CLI invocations.
• Frontend adapters stay thin: CLI, Feishu, MCP, and automation jobs parse channel-specific input and then hand work to daemon IPC or the task queue.
• Reasoning is separate from execution: AgentCore builds prompts and talks to the LLM; AgentKernel executes tools, checks permissions, routes paths, and compresses context.
• Remote workspace is a routing mode: remote mode changes where selected tools run; it is not a second agent stack.
• Release commits stay small: runtime architecture changes land as normal feature/fix commits before a release commit handles versioning and packaging.

Layer Map

Layer	Main modules	Owns	Should not own
Frontend	src/frontend/*, root shims	Channel parsing, display, callbacks	Agent state, direct tool execution
Automation	src/system/automation/*	IPC, queues, job definitions, session registry, scheduling	LLM prompt details
Kernel	src/system/kernel/*	Core pooling, kernel requests, terminal shell, summarization	Provider selection details
Agent runtime	src/agent_core/agent/*, src/agent_core/llm/*, src/agent_core/context/*	Agent loop, prompts, providers, memory/context state	Frontend transport details
Tools	src/agent_core/tools/*, src/system/tools/*, src/agent_core/mcp/*	Tool definitions, validation, execution, MCP proxying	Release packaging
Remote worker	src/macchiato_remote/*, src/agent_core/remote/*	Remote protocol, worker registry, workspace routing	Full bot daemon state

Tool Boundary

Tools are exposed to the LLM through the registry, but the kernel remains the authority for visibility, permission checks, path grants, local-vs-remote routing, and large-result handling. That keeps the LLM loop simple: it requests tool calls; the kernel decides how to execute them safely.

Runtime State

Generated state stays out of source control:

Path	Purpose
data/	persistent app data, sessions, automation repositories
logs/	daemon and gateway logs
.macchiato/	local command/job runtime state
dist/, build/, *.egg-info/	package build outputs
.venv/, .pytest_cache/, __pycache__/	local development artifacts

For the longer design notes and contribution placement rules, see docs/architecture.md.

Repository Map

src/
├── agent_core/          # Agent loop, prompts, memory, LLM providers, core tools
├── system/
│   ├── automation/      # Daemon runtime, IPC, queue, scheduler, repositories
│   ├── kernel/          # AgentKernel, KernelScheduler, CorePool, terminal
│   └── tools/           # App-level tools and tool registry assembly
├── frontend/            # CLI, Feishu, MCP, Canvas, Shuiyuan adapters
├── macchiato_bot_cli/   # Packaged CLI and daemon entrypoints
└── macchiato_remote/    # Remote worker protocol, CLI, runtime

packages/macchiato-remote/
└── pyproject.toml       # Worker-only PyPI package built from src/macchiato_remote

Quick Start From A Checkout

uv sync --all-groups
cp config/config.example.yaml config/config.yaml
cp .env.example .env

Fill provider keys in .env, then start the daemon:

uv run automation_daemon.py

In another terminal, start a frontend:

uv run main.py
uv run main.py "schedule a meeting tomorrow at 3pm"
uv run feishu_ws_gateway.py

source init.sh is optional. It runs uv sync, exports PYTHONPATH, and loads .env for the current shell.

Installed Commands

After installing macchiato-bot, use:

macchiato-daemon
macchiato
macchiato "schedule a meeting tomorrow at 3pm"
macchiato-remote status

The CLI is an IPC client. If the daemon is not running, it exits instead of starting a private agent process.

Common Slash Commands

CLI and Feishu share the same slash-command surface through daemon IPC:

• /help
• /model, /model list, /model <name>
• /session, /session whoami, /session list
• /session new [id], /session switch <id>, /session delete <id>
• /remote-use <login> [path]
• /remote-status
• /remote-release or /cloud-use

Remote Workspaces

Remote workspace mode lets a cloud-hosted daemon operate on a user-authorized folder on another machine. The full bot stays on the daemon host; the local machine runs only macchiato-remote, which exposes bash/file capabilities for that authorized workspace.

Read the setup, login modes, permission profiles, and troubleshooting notes in docs/remote-workspace.md.

Configuration

Main config lives at config/config.yaml; start from config/config.example.yaml. Provider fragments live under config/llm/providers.d/*.yaml.

Important areas:

Key	Purpose
llm.*	Active provider, vision provider, provider fragments, request defaults
agent.*	Iteration limits, subagent caps, working-set size
tools.*	Core tool exposure and template-based tool sets
memory.*	Working memory, recall policy, persistent memory
automation.jobs	Scheduled jobs managed by the daemon
command_tools.*	Bash enablement, workspace isolation, writable roots
file_tools.*	File read/write/modify controls
mcp.*	External MCP server configuration
feishu.*	Feishu app and gateway settings

Development

uv sync --all-groups
uv run pytest tests/ -v --tb=short
black --check src/ tests/
isort --check-only src/ tests/

Focused docs:

• Architecture
• Remote workspaces
• Feishu integration
• Deployment / systemd
• Release process
• Development guidelines

License

MIT