Agents & Tools

Core components for building intelligent agent workforces

Dotbase provides a comprehensive suite of agent types and tools for building sophisticated AI workforces. Built on Microsoft's Autogen framework, our components enable seamless integration and collaboration between different AI agents.

graph LR
    A[Interface] --> B[Hub]
    C[Agent] --> B
    D[GPTAgent] --> B
    E[Function] --> C & D
    style B fill:#2563eb,stroke:#1e40af,color:#fff
    style A fill:#059669,stroke:#047857,color:#fff
    style C fill:#7c3aed,stroke:#6d28d9,color:#fff
    style D fill:#7c3aed,stroke:#6d28d9,color:#fff
    style E fill:#ea580c,stroke:#c2410c,color:#fff

Agent Types

Nexus

A configurable ConversableAgent subclass designed for specialized tasks and workflows. This agent type serves as the foundation for creating specialized AI workers with defined roles and capabilities.

interface AgentConfig {
    name: string;
    systemPrompt: string;
    model: string;
    temperature?: number;
    maxTokens?: number;
    tools?: Function[];
}

Key Features

• Dynamic system prompt configuration for role definition

• Custom tool integration for enhanced capabilities

• Adjustable model parameters for response control

• Memory management for conversation context

• Task specialization through prompt engineering

• Real-time learning and adaptation

• Multi-step reasoning capabilities

• Error recovery and fallback strategies

Use Cases

• Data analysis and processing

• Content generation and editing

• Research assistance

• Code generation and review

• Technical documentation

• Problem-solving tasks

Lumina

Integration with NovaMind Assistant API for enhanced capabilities. This agent type leverages NovaMind specialized assistants with their unique capabilities and knowledge bases.

interface NovaMindAgentConfig {
    assistantId: string;
    name: string;
    tools: string[];
    model?: string;
    metadata?: Record<string, unknown>;
}

Capabilities

• NovaMind Assistant integration with custom configurations

• Specialized function support for complex tasks

• Advanced knowledge retrieval using NovaMind systems

• Code interpretation and execution

• File handling and analysis

• Multi-modal input processing

• Dynamic context management

• Integration with external tools and APIs

Applications

• Complex data analysis

• Natural language processing

• Code generation and debugging

• Document analysis and summary

• Mathematical computations

• API integration tasks

Bridge

Interface between human operators and AI agents. This component manages all human-AI interactions and feedback loops.

interface InterfaceConfig {
    name: string;
    humanFeedback: boolean;
    maxRetries?: number;
    feedbackType?: 'immediate' | 'batched';
}

Features

• Real-time feedback handling for continuous improvement

• Task delegation with priority management

• Result verification and quality assurance

• Error management and recovery

• Input validation and preprocessing

• Output formatting and presentation

• Session management and context preservation

• User preference handling

Interaction Modes

• Synchronous communication

• Asynchronous batch processing

• Interactive debugging

• Multi-step validation

• Progress monitoring

Synergy Hub

Orchestration hub for multi-agent collaboration. This central component manages agent interactions and workflow coordination.

interface HubConfig {
    agents: string[];
    maxRounds: number;
    enableMemory: boolean;
    timeoutSeconds?: number;
    adminAgent?: string;
}

Core Functions

• Agent communication routing

• Task distribution and load balancing

• Conversation flow management

• Memory synchronization

• Error handling and recovery

• Performance monitoring

• Resource allocation

• State management

Advanced Features

• Dynamic agent allocation

• Priority-based scheduling

• Conflict resolution

• Conversation checkpointing

• Performance optimization

• Security enforcement

Tools

Spark

Extensible function integration for enhanced agent capabilities. Functions serve as modular tools that agents can use to perform specific tasks.

def function(
    param1: str,
    param2: List[str],
    **kwargs
) -> Dict[str, Any]:
    """
    Function template for custom tool integration.
    
    Args:
        param1: Primary parameter
        param2: List of secondary parameters
        **kwargs: Additional parameters
        
    Returns:
        Dict containing operation results
    """
    results = {}
    # Implementation
    return results

Features

• Custom Python function integration

• NovaMind function calling support

• Error handling and validation

• Input/output type safety

• Performance monitoring

• Resource management

• Asynchronous execution

• Retry mechanisms

Implementation Examples

Data Analysis Pipeline

sequenceDiagram
    participant I as Interface
    participant H as Hub
    participant A as Agent
    participant F as Function
    
    I->>H: Analysis Request
    H->>A: Delegate Task
    A->>F: Process Data
    F-->>A: Results
    A->>H: Analysis
    H->>I: Final Report

Configuration Best Practices

# Agent Configuration
agent_config = {
    "system_prompt": """
    Role: Data Analysis Specialist
    Objective: Process and analyze complex datasets
    Constraints:
    - Validate input data
    - Handle missing values
    - Provide statistical significance
    """,
    "model": "gpt-4",
    "temperature": 0.7,
    "tools": ["data_processor", "statistical_analyzer"]
}

# Error Handling
error_config = {
    "max_retries": 3,
    "retry_delay": "exponential",
    "fallback_strategy": "default_response",
    "logging": "verbose"
}

Security & Performance

Feature	Implementation
Authentication	OAuth 2.0 / JWT
Rate Limiting	Token bucket algorithm
Monitoring	Prometheus metrics
Logging	Structured JSON logs
Caching	Redis with LRU policy