App

Introduction

The app serves as a showcase for the Rust-based framework designed to interact with multiple AI agents. The framework provides an extensible and modular architecture, allowing users to instantiate, interact with, and manage different types of AI-driven agents with ease.

Features

Multi-Agent Management

• The framework supports multiple agents, each with its own distinct personality and capabilities.
• Agents can be dynamically added, removed, and modified.

Versatile Agent Roles

• Agents can function in different modes:
  • Chat Mode: Standard AI conversation.
  • Coder Mode: AI optimized for programming-related interactions.
  • Twitter Mode: AI tailored for social media interactions.
• The ability to switch between these modes dynamically allows for flexible usage.

Import & Export Functionality

• Agents can be saved and loaded from files, allowing users to persist and restore configurations.
• Supports easy integration with external data sources.

Demonstration

Running the Showcase

1. Startup: Running the program initializes a list of AI agents and prints the system logo.
2. Agent Interaction:
   • Users can chat with an agent by specifying its index.
   • They can switch between different agent roles dynamically.
3. Data Persistence:
   • Agents can be exported for future use.
   • Previously saved agents can be imported and used immediately.

Example Commands

• chat 0 – Start chatting with agent at index 0.
• convert to coder 0 – Convert agent 0 to coder mode.
• export 0 – Save agent 0 to a file.
• import dummy.agent – Load an agent from a file.
• quit – Exit the application.

Conclusion

This showcases some capabilities of the Rust framework for AI agent interaction. By providing a structured and extensible approach to managing intelligent agents, it opens the door for numerous real-world applications, from automation to AI-powered assistance.