aevatar-Framework

Overview Architecture Documentation for aevatar Framework#

Repos: https://github.com/aevatarAI/aevatar-framework

Introduction#

The aevatar Framework is designed to facilitate the development of intelligent agents that can interact with various environments and perform tasks autonomously. This framework provides a structured approach to building, deploying, and managing AI agents.

High-Level Architecture#

The architecture of the aevatar Framework can be divided into several key components:

  • Core Components: These include the foundational classes and interfaces that define the behavior and capabilities of agents.
  • Agent Interfaces: Interfaces like IAIGAgent define the contract for agent behavior, ensuring consistency across different agent implementations.
  • Publishing Mechanism: Components like GAgentBase.Publish handle the communication and publishing of agent actions and states.
  • Key Components
  • GAgentBase: This is a base class for agents that provides common functionalities and properties. It may include methods for publishing actions and states to other components or systems.
    • PublishAsync Method: This method is responsible for asynchronously publishing the agent's state or actions to a designated endpoint or service.
  • IAIGAgent Interface:
    • Defines essential methods that any AI agent must implement.
  • Data Flow
  • Agent Interactions: Agents communicate with each other and with external systems through well-defined interfaces and methods.
  • Event Publishing: Agents publish events and states using mechanisms defined in classes like GAgentBase, which can be subscribed to by other components.
  • Design Considerations
  • Scalability: The framework is designed to support multiple agents operating concurrently, allowing for scalable solutions.
  • Extensibility: New agent types can be easily added by implementing the defined interfaces.
  • Conclusion

    • The aevatar Framework provides robust architecture for developing AI agents. The use of interfaces and base classes facilitates a modular and extensible design, enabling developers to create intelligent agents efficiently.

    Edited on: 3 March 2025 12:00:59 GMT+0