File-based Multi-agent Task Management Reference Architecture
A reference architecture for a multi-agent system that utilizes file-based communication to manage and execute tasks efficiently.
This blueprint outlines a reference architecture for a sophisticated AI multi-agent system designed to manage and execute tasks through file-based communication.
The architecture features two specialized agents: a Manager agent responsible for overseeing task coordination and a Worker agent dedicated to executing assigned tasks. Communication between these agents is facilitated via a shared file resource (a todo), enabling efficient task management and execution.
The Manager agent is connected to a trigger integration that responds to external events, allowing it to dynamically assign tasks to the Worker agent based on real-time requirements. The Worker agent, on the other hand, is configured with a timer-based trigger integration that activates it at regular intervals to check for and process assigned tasks.
This architecture exemplifies the effective use of shared resources for inter-agent communication and coordination. By leveraging file-based task lists, the system ensures that both agents can operate asynchronously while maintaining a clear and organized workflow. The modular design allows for easy scalability and adaptability, making it suitable for various task management scenarios in dynamic environments.
Skillset
This example uses a dedicated Skillset. Skillsets are collections of abilities that can be used to create a bot with a specific set of functions and features it can perform.
Execute Task Operation
A function that executes an operation on the task catalogue.Execute Task Operation
A function that executes an operation on the task catalogue.
Terraform Code
This blueprint can be deployed using Terraform, enabling infrastructure-as-code management of your ChatBotKit resources. Use the code below to recreate this example in your own environment.
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