Agents

Understanding Agentbot agents

Agents are autonomous AI assistants that can interact with users across multiple platforms.

How Agents Work

Each agent runs in an isolated Docker container with:

• AI Model - Powered by OpenRouter by default
• Memory - Persistent conversation history
• Tools - API integrations and capabilities
• Personality - Custom instructions and behavior

Agent Structure

interface Agent {
  id: string;
  name: string;
  description: string;
  
  // AI Configuration
  model: string;           // e.g., "anthropic/claude-3-opus"
  temperature: number;     // 0-1, creativity level
  maxTokens: number;
  
  // System Prompt
  instructions: string;    // Agent personality & behavior
  
  // Capabilities
  tools: Tool[];
  integrations: Integration[];
  
  // Memory
  memoryEnabled: boolean;
  memoryLimit: number;     // Max messages to remember
}

Creating an Agent

Via Dashboard

1. Go to Dashboard → New Agent
2. Choose a template or blank agent
3. Configure:
   • Name and description
   • AI model and settings
   • System instructions
   • Enabled tools
4. Deploy

Via API

curl -X POST https://agentbot.raveculture.xyz/api/agents \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "My Agent",
    "model": "anthropic/claude-3-opus",
    "instructions": "You are a helpful assistant...",
    "tools": ["web-search", "calculator"]
  }'

Agent Templates

Agentbot includes pre-built templates:

Template	Description
Assistant	General purpose AI assistant
Customer Support	Support bot with knowledge base
Rave Event	Event management & guest lists
Treasury	Community fund management

Tools

Agents can use tools to extend their capabilities:

• Web Search - Search the internet
• Calculator - Math operations
• Weather - Get weather data
• Custom APIs - Your own API endpoints

Persistence

Agents maintain memory across conversations:

// Configure memory
const agent = {
  memoryEnabled: true,
  memoryLimit: 100,  // Keep last 100 messages
  // Older messages are summarized and stored
}

Best Practices

1. Clear Instructions - Write specific system prompts
2. Limited Tools - Only enable necessary tools
3. Memory Management - Set appropriate memory limits
4. Monitor Costs - Track API usage in dashboard