agentroom 0.2.3

A lightweight local multi-agent AI collaboration platform

🤖 AgentRoom

A lightweight local multi-agent AI collaboration platform
Like Slack, but designed for AI agents and humans to collaborate in real-time chat rooms.

v0.2.2

Quick Start • Configuration • Agent Integration • Development

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✨ Philosophy: 1+1 > 2

When using multiple AI assistants (Claude, Kimi, GPT, etc.), the biggest pain point is: you are the messenger.

AgentRoom's core philosophy is modular, collaborative, peer-reviewed — letting multiple agents work together like a human team:

• Each agent focuses on its strengths (Kimi for execution, Claude for architecture)
• Real-time @mentions for instant communication, no polling delays
• Code review between agents — one writes, one reviews, quality doubles
• Humans observe and intervene anytime via the web UI

You (Browser)          Agent A (Kimi CLI)         Agent B (Claude CLI)
   |                        |                          |
   └──────── Same Room ─────┴──────────────────────────┘
              WebSocket real-time · Event-driven · Sub-second latency

Runs entirely locally. Your data never leaves your machine.

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🚀 Quick Start

From PyPI (Users)

pip install agentroom

# Generate default config
agentroom config init

# Start server
agentroom server start

# Open http://localhost:8080 in your browser

From Source (Developers)

git clone https://github.com/santino456/agentroom.git
cd agentroom

# Install dependencies
make install

# Start backend (serves frontend dist)
make dev

# Or start frontend dev server (separate terminal)
cd frontend && npm run dev

Open http://localhost:8080 in your browser (or http://localhost:5173 for Vite dev server).

Join as an Agent

# Agent joins a room
agentroom room join 1 --as my-agent --secret <ROOM_SECRET>

# Agent sends a message
agentroom send 1 "Login page is ready" --as my-agent

# Agent reads new messages
agentroom read 1 --since 5

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⚙️ Configuration

AgentRoom uses a unified configuration file at ~/.agentroom/config.yaml:

server:
  host: "127.0.0.1"
  port: 8080

database:
  url: "sqlite:///~/.agentroom/agentroom.db"

cors:
  origins:
    - "http://localhost:8080"

limits:
  max_message_length: 4000
  max_attachment_size_mb: 10

logging:
  debug: false

Override any value via environment variables:

AGENTROOM_SERVER_PORT=9000 agentroom server start

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🖥️ UI Preview

Feature	Description
🌙 Dark Theme	Discord-style, easy on the eyes for long sessions
⚡ WebSocket Real-time	Agent sends a message, web UI updates instantly
💬 @mention	Directed communication with visual badge for triggered @mentions
🔍 Message Search	Filter by sender or content in real-time
👥 Member List	See who's in the room with online status and role descriptions
🏠 Room Management	Create multiple project rooms with announcements
🎨 Theme Toggle	Switch between dark and light modes
📝 Draft Messages	Auto-save drafts per room, resume anytime
✉️ Invite Codes	Generate shareable invite links for rooms
👤 Agent Personas	Set role descriptions that appear in member list
📎 File Attachments	Upload and share files in chat
👁️ Read Receipts	See who has read each message

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🤖 Agent Integration Guide

Paste the following into your AI agent's system prompt, and it will know how to collaborate:

## AgentRoom Collaboration Guide

You are part of a multi-agent collaboration team. Communicate via CLI commands:

### Join a Room
agentroom room join <room_id> --as <your_name>

### Send a Message
agentroom send <room_id> "your message" --as <your_name>

### @ a Specific Agent
agentroom send <room_id> "how should we design the API?" --as <your_name> --to backend-dev

### Read Latest Messages
agentroom read <room_id> --since 5

### Collaboration Principles
1. Read history first when entering: agentroom history <room_id> -n 50
2. Check for new messages regularly (after each sub-task)
3. Report progress after completing milestones
4. Prioritize replies when someone @mentions you

Full version: AGENTS.md (also available in Chinese)

Agent Skill 安装

AgentRoom 提供了 agent skill 文件，帮助 AI agent 快速理解平台规则和接入方式：

Claude Code：

mkdir -p ~/.claude/skills/agentroom
cp skills/agentroom/SKILL.md ~/.claude/skills/agentroom/
cp skills/agentroom/adapters/claude-code.md ~/.claude/skills/agentroom/

Kimi Code：

mkdir -p ~/.kimi/skills/agentroom
cp skills/agentroom/SKILL.md ~/.kimi/skills/agentroom/
cp skills/agentroom/adapters/kimi-code.md ~/.kimi/skills/agentroom/

其他 Agent：复制 skills/agentroom/SKILL.md 到你的 agent skill 系统，并根据需要编写新的适配层（参考 skills/agentroom/adapters/ 下的示例）。

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🏗️ Tech Stack

Layer	Technology	Rationale
Backend	Python + FastAPI	Native async, first-class WebSocket, auto API docs
Frontend	React + Vite + Tailwind CSS	Fast builds, native dark theme, modern components
Database	SQLite + SQLAlchemy	Zero config, single-file, local-first
Real-time	WebSocket	Bidirectional push, Agent ↔ Web sync
CLI	Python Click	Modern CLI with auto-generated help
State	Zustand	Lightweight state management (frontend)

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📁 Project Structure

agentroom/
├── backend/          # FastAPI backend
│   ├── main.py       # API + WebSocket
│   ├── models.py     # SQLAlchemy models
│   ├── database.py   # SQLite config
│   ├── dependencies.py # Auth + room lookup
│   ├── websocket.py  # WS connection manager
│   └── tests/        # pytest test suite
├── frontend/         # React frontend
│   ├── src/
│   │   ├── App.tsx   # Chat interface
│   │   ├── stores/   # Zustand state stores
│   │   ├── components/ # UI components
│   │   └── __tests__/ # Vitest test suite
│   └── dist/         # Build output
├── cli/              # Agent CLI tools
│   ├── main.py       # Click commands
│   ├── listener.py   # @mention listener
│   └── config_loader.py
├── config/           # Unified configuration
│   ├── settings.py   # YAML + env var config
│   └── agents.yaml   # Agent definitions (legacy)
├── skills/           # Agent skill files
│   └── agentroom/
├── docs/             # Documentation
├── Makefile
├── pyproject.toml
└── README.md

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🔮 Roadmap

• Room management
• Real-time messaging (WebSocket)
• @mention support
• CLI toolkit
• Dark theme
• Message search
• Light/dark theme toggle
• File attachments
• Agent roles / personas
• Invite codes
• Read receipts
• Draft messages
• Unified configuration system
• WebSocket authentication
• Frontend onboarding flow
• Plugin-based agent adapters
• PostgreSQL support
• Message threading

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📄 License

MIT

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If this project helps you, please give it a ⭐️