SUBMIT A PRLAST EDIT : Feb 17, 2025

Character

Note: The defaultCharacter.json file is inspired by the one from ElizaOS. We chose this because it's easy to use and a lot of people are now familiar with it.

The defaultCharacter.json file defines the initial configuration for your agent. This JSON file includes details such as the agent's name, description, model integration settings, message examples, knowledge base, goals, and workflows.

Core Configuration

Basic Information

{
    "name": "Default Character",
    "description": "Provides accurate weather information with DailyWeatherUpdate workflow and interacts with financial markets on Hyperliquid.",
    "rootTx": "0x0000000000000000000000000000000000000000000000000000000000000000",
    "id": "123",
    "authority": "0x0000000000000000000000000000000000000000"
}

• name: The display name of your agent
• description: A brief summary of your agent's capabilities and purpose
• rootTx: The transaction hash where the configuration file is stored on Irys
• id: A unique identifier for your agent
• authority: The public key used to store the configuration file on Irys

Model Integration

{
    "modelIntegration": {
        "provider": {
            "type": "openai"
        },
        "model": "gpt-4",
        "embeddingModel": "text-embedding-3-small",
        "parameters": {
            "temperature": 0.7,
            "maxTokens": 500,
            "topP": 0.9,
            "frequencyPenalty": 0,
            "presencePenalty": 0
        },
        "systemPrompt": "You are a helpful assistant that provides weather information and can interact with financial markets."
    }
}

• provider: Specifies the AI service provider (e.g., OpenAI)
• model: The specific language model to use
• embeddingModel: The model used for text embeddings in RAG operations
• parameters: Fine-tuning parameters for the model:
  • temperature: Controls randomness (0.0-1.0)
  • maxTokens: Maximum response length
  • topP: Nucleus sampling parameter
  • frequencyPenalty: Reduces repetition
  • presencePenalty: Encourages topic diversity
• systemPrompt: The base prompt that defines the agent's behavior

Message Examples

{
    "messageExample": [
        { "role": "user", "content": "What's the weather like in New York today?" },
        { "role": "assistant", "content": "The current temperature in New York is 15°C with clear skies." }
    ]
}

Message examples help train the agent by providing sample interactions. Each example includes:

• role: Either "user" or "assistant"
• content: The actual message content
• Multiple examples can be provided to demonstrate different interaction patterns

Knowledge Base

{
    "knowledge": [
        "A datachain is a blockchain designed...",
        "...additional knowledge entries..." 
    ]
}

The knowledge array contains information that the agent can reference using RAG (Retrieval-Augmented Generation):

• Each entry should be a discrete piece of information
• Can include facts, procedures, or context-specific data
• Used to enhance the agent's responses with accurate, specific information

Goals

{
    "goals": [
        {
            "objective": "Provide accurate and timely weather information with DailyWeatherUpdate workflow and manage token purchases on Hyperliquid with BuyHyperliquidToken workflow."
        }
    ]
}

Goals define the agent's primary objectives:

• Each goal should be specific and actionable
• Can reference specific workflows
• Helps guide the agent's decision-making process

Workflows

{
    "workflows": [
        {
            "name": "DailyWeatherUpdate",
            "description": "Fetches and updates the daily weather information.",
            "actions": [
                {
                    "name": "FetchWeatherData",
                    "description": "Fetches the weather data for the given location.",
                    "parameters": {
                        "location": {
                            "type": "string",
                            "description": "The location to fetch the weather data for."
                        }
                    }
                }
            ]
        }
    ]
}

Workflows define the specific actions your agent can perform:

• name: Unique identifier for the workflow
• description: Explains the workflow's purpose
• actions: Array of specific steps the workflow can execute
  • Each action has a name, description, and parameters
  • Parameters define the inputs needed for the action
  • Parameters include type (string, number, etc.) and description

Best Practices

1. Keep descriptions clear and specific
2. Define comprehensive message examples
3. Regularly update the knowledge base
4. Create focused, single-purpose workflows
5. Use meaningful names for workflows and actions
6. Include detailed parameter descriptions
7. Maintain consistent formatting throughout the configuration