[Roadmap] Multi-Agent System Based On The Role-Playing Module

[Appointat]

Roadmap for MAS

• Reasoning type (reviewing)
• Task breakdown (dev done)
• Insight agent (dev done)
• Env management (storage+retrieval, dev done)
• Execution order (dev done)
• Demo: multi-agent communication (dev done)
• Format output (dev done)
• Documentation
• Fonction calls integration (Google, wiki, duckduckgo, etc.. reviewing)
• UI dev (dev done)

Additional context

Adding a multi-agent feature aligns with our long-term vision of creating a more robust and versatile system that can cater to a wider range of use cases.

Related Issues or PRs:

• Automatic Role Generation with Descriptions for Two Roles
• feat: Multi-Agent System Based On The Role-Playing Module #346
• [Feature Request] Improvement in Insight Extraction for Long Texts #321
• [Feature Request] Enhancing the Deductive Reasoning Capabilities of the "Deductive Reasoner Agent" with Mathematical Modeling #314
• Reasoning type: React in Camel
• DuckDuckGo API

Motivation

Issue Summary:
Implement a multi-agent functionality to enhance collaboration and coordination among different agents within the system.

Detailed Description:
Currently, our system operates with a single-agent or double-agent approach, which limits its capabilities in scenarios where multiple agents need to interact and collaborate. To address this limitation, we propose implementing a multi-agent feature that allows the system to support multiple agents working together.

Expected Benefits:

1. Improved Collaboration: Agents can work together on complex tasks, leveraging each other's strengths.
2. Enhanced Efficiency: Task distribution and resource sharing can lead to better resource utilization and faster task completion.
3. Scalability: The system will be better prepared to handle larger and more intricate operations.

Solution

Key Components:

• Agent Interaction: Define mechanisms for agents to communicate and share information.
• Coordination Algorithms: Develop algorithms to facilitate coordination, task assignment, and resource sharing among agents.
• Testing and Validation: Ensure the feature works seamlessly in various scenarios and doesn't negatively impact existing functionalities.

Alternatives

In our quest to enhance collaboration and coordination among agents, we explored alternative solutions to task allocation. Two prominent approaches we considered are:

Gantt Chart for Task Scheduling: Using Gantt charts, we could visually plan and allocate tasks to agents over time. Gantt charts offer a clear representation of task dependencies, durations, and resource allocations, enabling efficient scheduling.

Directed Graph for Dependency Management: Directed graphs can depict task dependencies and relationships between agents. By modeling the tasks and their dependencies as a directed graph, we can employ graph algorithms to optimize task allocation and minimize delays.

[Wendong-Fan]

@Appointat need to break down into smaller items