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
- Startup: Running the program initializes a list of AI agents and prints the system logo.
- Agent Interaction:
- Users can chat with an agent by specifying its index.
- They can switch between different agent roles dynamically.
- 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.