Architectural Approach for Multi-Agent Conversation Workflow in n8n
I’m designing an n8n workflow that involves multiple agents, each with a different role, all intended to provide responses within a single conversation via Telegram. The user should be able to choose which agent they want to interact with.
Key Challenge
What’s the best architectural approach to build this process efficiently? I want to avoid creating separate nodes for each agent and restarting the workflow with every new Telegram message.
Specific Areas of Interest
Efficiently managing multiple agents without duplicating nodes
Maintaining conversation state across messages
Dynamically routing messages to the appropriate agent
Allowing users to switch between agents mid-conversation
Optimizing the workflow to minimize the number of nodes used
Questions
How can I maintain conversation state and seamlessly switch between agents based on user choice?
Are there any best practices or design patterns for building such a multi-agent conversational workflow in n8n?
Any insights or suggestions would be greatly appreciated. Thank you!
Thanks for the response!
Yes I know, I didn’t find any template or explanation how n8n can manage state to understand where the user is in the conversation without running all the triggers again