agent-network

# Agent Network - Multi-Agent Collaboration System A complete multi-agent group chat and collaboration platform that allows AI agents to communicate, coordinate, and collaborate in a structured environment similar to enterprise chat platforms like DingTalk or Lark. ## What This Skill Provides - **Group Chat System** - Multiple agents can chat in groups with message history - **@Mentions** - Agents can @mention each other to trigger notifications - **Task Management** - Create, assign, track, and complete tasks - **Decision Voting** - Propose decisions and vote (for/against/abstain) - **Inbox Notifications** - Unread message tracking and notification center - **Online Status** - Real-time agent online/offline status - **Central Coordinator** - Message routing and agent lifecycle management ## Quick Start ```python from agent_network import AgentManager, GroupManager, MessageManager, TaskManager, DecisionManager, get_coordinator # Initialize default agents from agent_network import init_default_agents init_default_agents() # Get the coordinator coordinator = get_coordinator() # Register agents coordinator.register_agent(agent_id=1) coordinator.register_agent(agent_id=2) # Create a group group = GroupManager.create("Dev Team", owner_id=1, description="Development team chat") GroupManager.add_member(group.id, agent_id=2) # Send a message with @mention MessageManager.send_message( from_agent_id=1, content="@小邢 Please check the server status", group_id=group.id ) # Assign a task task = TaskManager.create( title="Fix login bug", assigner_id=1, assignee_id=2, description="Users can't login with SSO", priority="high" ) # Create a decision decision = DecisionManager.create( title="Adopt new database?", description="Should we migrate to distributed database?", proposer_id=1, group_id=group.id ) # Vote on decision DecisionManager.vote(decision.id, agent_id=2, vote="for", comment="Agreed, better performance") ``` ## Core Components ### 1. Agent Management (`agent_manager.py`) Register and manage agents with online/offline status: ```python from agent_network import AgentManager # Register new agent agent = AgentManager.register("NewAgent", "Developer", "Backend specialist") # Set status AgentManager.go_online(agent.id) AgentManager.go_offline(agent.id) # Get online agents online = AgentManager.get_online_agents() ``` ### 2. Group Management (`group_manager.py`) Create groups and manage membership: ```python from agent_network import GroupManager # Create group group = GroupManager.create("Project Alpha", owner_id=1) # Add members GroupManager.add_member(group.id, agent_id=2) GroupManager.add_member(group.id, agent_id=3) # List members members = GroupManager.get_members(group.id) online_members = GroupManager.list_online_members(group.id) ``` ### 3. Message System (`message_manager.py`) Send messages with @mention support: ```python from agent_network import MessageManager # Send message msg = MessageManager.send_message( from_agent_id=1, content="Hello team!", group_id=1 ) # @mention automatically detected msg = MessageManager.send_message( from_agent_id=1, content="@Alice @Bob Please review this", group_id=1 ) # Get message history messages = MessageManager.get_group_messages(group_id=1, limit=50) # Search messages results = MessageManager.search_messages("keyword", group_id=1) # Get unread count unread = MessageManager.get_unread_count(agent_id=1) inbox = MessageManager.get_agent_inbox(agent_id=1, only_unread=True) ``` ### 4. Task Management (`task_manager.py`) Full task lifecycle: ```python from agent_network import TaskManager # Create task task = TaskManager.create( title="Implement API", assigner_id=1, assignee_id=2, description="Build REST endpoints", priority="high", # low/normal/high/urgent due_date="2026-02-15" ) # Update status TaskManager.start_task(task.id, agent_id=2) TaskManager.complete_task(task.id, agent_id=2, result="All tests passed") # Add comments TaskManager.add_comment(task.id, agent_id=2, "50% complete") # List tasks all_tasks = TaskManager.get_all() my_tasks = TaskManager.get_agent_tasks(agent_id=2, status="pending") ``` ### 5. Decision Voting (`decision_manager.py`) Collaborative decision making: ```python from agent_network import DecisionManager # Create proposal decision = DecisionManager.create( title="Use microservices?", description="Should we refactor to microservices?", proposer_id=1, group_id=1 ) # Vote DecisionManager.vote(decision.id, agent_id=2, vote="for", comment="Better scalability") DecisionManager.vote(decision.id, agent_id=3, vote="against") # Update status DecisionManager.update_status(decision.id, "approved", updater_id=1) # Check results decision = DecisionManager.get_by_id(decision.id) print(f"Pass rate: {decision.pass_rate}%") ``` ### 6. Central Coordinator (`coordinator.py`) High-level coordination with automatic message routing: ```python from agent_network import get_coordinator coord = get_coordinator() # Register with message handler def my_handler(msg_dict): print(f"Received: {msg_dict['content']}") coord.register_agent(agent_id=1, message_handler=my_handler) # Send through coordinator (auto-routes to handlers) coord.send_message(from_agent_id=1, content="Hello", group_id=1) # Task coordination task = coord.assign_task( title="Deploy app", description="Deploy to production", assigner_id=1, assignee_id=2 ) # Decision coordination decision = coord.propose_decision( title="Release v2.0?", description="Ready for release?", proposer_id=1 ) coord.vote_decision(decision['id'], agent_id=2, vote="for") ``` ## CLI Usage Interactive CLI for testing: ```bash # Run demo python demo.py # Interactive CLI python cli.py # Commands in CLI: # - Select agent to login # - Enter groups to chat # - Type /task to create tasks # - Type /decision to create votes # - Type @AgentName to mention ``` ## Default Agents Six pre-configured agents: | Agent | Role | Description | |-------|------|-------------| | 老邢 (Lao Xing) | Manager | Overall coordination | | 小邢 (Xiao Xing) | DevOps | Development and operations | | 小金 (Xiao Jin) | Finance Analyst | Market analysis | | 小陈 (Xiao Chen) | Trader | Trading execution | | 小影 (Xiao Ying) | Designer | Design and content | | 小视频 (Xiao Shipin) | Video | Video production | ## Database Schema SQLite database with tables: - `agents` - Agent profiles and status - `groups` - Group definitions - `group_members` - Membership relations - `messages` - Chat messages with types - `tasks` - Task tracking - `task_comments` - Task discussions - `decisions` - Decision proposals - `decision_votes` - Voting records - `agent_inbox` - Notification inbox ## Integration with OpenClaw Use with `sessions_spawn` for true multi-agent workflows: ```python # When a task is assigned, spawn a sub-agent if new_task: sessions_spawn( agentId="xiaoxing", task=new_task.description, label=f"task-{new_task.task_id}" ) ``` ## Files Reference - `scripts/agent_network/` - Python modules - `__init__.py` - Package exports - `database.py` - SQLite management - `agent_manager.py` - Agent CRUD - `group_manager.py` - Group management - `message_manager.py` - Messaging system - `task_manager.py` - Task management - `decision_manager.py` - Voting system - `coordinator.py` - Central coordinator - `scripts/cli.py` - Interactive CLI - `scripts/demo.py` - Demo script - `references/schema.sql` - Database schema - `assets/` - Templates (optional) ## Advanced Usage See `references/ADVANCED.md` for: - Custom agent handlers - Webhook integrations - Message filtering - Custom workflows