Overview

Agent development in ElizaOS involves creating intelligent, autonomous entities that can interact with users, perform actions, and maintain persistent memory. The framework provides a complete toolkit for building sophisticated agents with personality, knowledge, and capabilities.

Core Components

Character Definition

Learn more about Character Definition →

Character definitions are JSON-based configurations that define an agent's personality, knowledge, and behavior:

Character Schema:

interface Character {
  name: string;
  bio: string[];
  lore: string[];
  knowledge: string[];
  messageExamples: MessageExample[][];
  postExamples: string[];
  topics: string[];
  style: {
    all: string[];
    chat: string[];
    post: string[];
  };
  adjectives: string[];
  settings?: {
    secrets?: { [key: string]: string };
    voice?: { model: string };
  };
}

Key Features:

• Personality Definition: Bio, lore, and behavioral traits
• Knowledge Base: Domain-specific information and facts
• Communication Style: Tone, language patterns, and response styles
• Example Conversations: Training data for consistent responses
• Voice Configuration: Text-to-speech and audio settings

Actions

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Actions are executable behaviors that agents can perform in response to user interactions or system events:

Action Interface:

interface Action {
  name: string;
  description: string;
  validate: (runtime: IAgentRuntime, message: Memory) => Promise<boolean>;
  handler: (runtime: IAgentRuntime, message: Memory) => Promise<boolean>;
  examples: ActionExample[][];
}

Built-in Actions:

• Message Processing: Text analysis and response generation
• Media Handling: Image, audio, and video processing
• Web Integration: API calls and web scraping
• File Operations: Document processing and management
• Social Media: Platform-specific interactions

Custom Actions:

• Plugin-based extensibility
• Event-driven execution
• Context-aware processing
• Memory integration

Evaluators

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Evaluators assess situations and determine appropriate responses:

Evaluator Interface:

interface Evaluator {
  name: string;
  description: string;
  similes: string[];
  examples: EvaluatorExample[];
  handler: (runtime: IAgentRuntime, message: Memory) => Promise<string>;
  validate: (runtime: IAgentRuntime, message: Memory) => Promise<boolean>;
}

Evaluation Types:

• Sentiment Analysis: Emotional tone detection
• Intent Recognition: Purpose and goal identification
• Context Assessment: Situational understanding
• Response Appropriateness: Content and timing evaluation
• Trust Scoring: Relationship and credibility assessment

Providers

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Providers integrate external services and data sources:

Provider Interface:

interface Provider {
  get: (runtime: IAgentRuntime, message: Memory) => Promise<string>;
}

Provider Types:

• Time Provider: Current time and scheduling information
• Facts Provider: Verified information and knowledge
• Browser Provider: Web search and content retrieval
• Wallet Provider: Cryptocurrency and token information
• Database Provider: Persistent data storage and retrieval

Tasks

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Tasks manage long-running operations and background processes:

Task Interface:

interface Task {
  id: UUID;
  name: string;
  description: string;
  status: "pending" | "running" | "completed" | "failed";
  handler: (runtime: IAgentRuntime) => Promise<void>;
}

Task Management:

• Scheduling: Cron-like scheduling for recurring tasks
• Queue Management: Priority-based task execution
• Error Handling: Retry logic and failure recovery
• Progress Tracking: Status monitoring and reporting

Agents

Learn more about Agents →

Agents are complete instances combining all components:

Agent Runtime:

• Initialization: Character loading and plugin registration
• Message Processing: Intelligent conversation handling
• Memory Management: Persistent state and knowledge
• Action Execution: Behavior implementation
• Learning: Continuous improvement from interactions

Development Workflow

1. Character Creation

Start by defining your agent's personality and knowledge:

# Create a new character file
elizaos create my-agent --character

# Edit character definition
{
  "name": "Assistant",
  "bio": ["I am a helpful AI assistant"],
  "knowledge": ["I know about programming and technology"],
  "style": {
    "all": ["Be helpful and informative"],
    "chat": ["Use conversational tone"]
  }
}

2. Plugin Development

Extend agent capabilities with custom plugins:

# Create a new plugin
elizaos create my-plugin --type plugin

# Plugin structure
src/
├── index.ts          # Plugin exports
├── actions/          # Custom actions
├── evaluators/       # Custom evaluators
├── providers/        # Custom providers
└── services/         # Custom services

3. Local Development

Test and iterate on your agent:

# Start development server
elizaos dev --character my-agent.json

# Hot reload enabled
# Real-time testing
# Debug logging

4. Testing

Comprehensive testing framework:

# Run tests
elizaos test

# Test types
├── unit/             # Component testing
├── integration/      # Feature testing
└── e2e/             # End-to-end testing

5. Deployment

Deploy your agent to production:

# Build for production
elizaos start --build

# Deploy to cloud
elizaos deploy --platform docker

# Monitor performance
elizaos logs --follow

Best Practices

Character Design

1. Consistent Personality: Maintain consistent tone and behavior
2. Rich Knowledge: Provide comprehensive domain knowledge
3. Clear Examples: Use diverse conversation examples
4. Appropriate Style: Match communication style to use case

Action Implementation

1. Validate Input: Always validate user inputs
2. Handle Errors: Implement graceful error handling
3. Context Awareness: Use conversation context effectively
4. Performance: Optimize for response time

Memory Management

1. Structured Storage: Organize information logically
2. Relevance Scoring: Prioritize important information
3. Cleanup: Remove outdated or irrelevant data
4. Privacy: Respect user privacy and data protection

Plugin Development

1. Single Responsibility: Each plugin should have a clear purpose
2. Configuration: Use environment variables for settings
3. Dependencies: Minimize external dependencies
4. Documentation: Provide clear documentation and examples

Advanced Features

Multi-Agent Systems

• Agent Communication: Inter-agent messaging and coordination
• Role Specialization: Agents with specific expertise
• Workflow Orchestration: Complex multi-step processes
• Resource Sharing: Shared memory and knowledge bases

Learning and Adaptation

• Conversation Learning: Improve responses based on feedback
• Knowledge Updates: Dynamic knowledge base updates
• Behavior Adaptation: Adjust behavior based on user preferences
• Performance Optimization: Continuous improvement metrics

Integration Patterns

• API Integrations: Connect with external services
• Database Connections: Persistent data storage
• Real-time Updates: WebSocket and event-driven updates
• Platform Deployment: Multi-platform deployment strategies

Troubleshooting

Common Issues

1. Memory Leaks: Monitor memory usage and cleanup
2. Performance Issues: Profile and optimize critical paths
3. Plugin Conflicts: Manage plugin dependencies
4. Character Inconsistency: Review and refine character definitions

Debugging Tools

• Debug Logging: Detailed execution traces
• Memory Inspector: Memory usage analysis
• Performance Profiler: Bottleneck identification
• Error Tracking: Comprehensive error monitoring

This comprehensive approach to agent development ensures you can create sophisticated, reliable, and engaging AI agents that provide value to users while maintaining consistent performance and behavior.