Community Contributed Multi-Agent Conversation

Name: Community Contributed Multi-Agent Conversation
Rating: 1.0 (1 reviews)
Author: Free N8N

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Community Templatesaiautomationchatbotconversationllmmulti-agent

Facilitates multi-agent conversations with AI, handling mentions and memory.

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About This Workflow

Overview

This workflow orchestrates a multi-agent conversation system. It allows for user input to trigger interactions with multiple AI agents. The system can extract mentions to direct messages to specific agents or, if no mentions are found, it will distribute the input among all agents in a randomized order. It also incorporates a memory buffer to maintain context.

Key Features

Dynamic agent routing based on mentions or randomized distribution.
System message customization for agents.
Basic memory management for conversation context.
Extensible with different AI models and agents.

How To Use

Import this workflow into your n8n instance.
Configure the 'Define Global Settings' and 'Define Agent Settings' nodes with your desired global parameters and individual agent configurations (including API keys or model names).
Set up the 'When chat message received' node to listen for incoming messages (e.g., via webhook).
Adjust the 'Simple Memory' node's sessionKey if you are using custom credentials for memory storage.
Trigger the workflow manually or via a chat interface to begin the conversation.

Apps Used

automation

chatbot

conversation

llm

multi-agent

Workflow JSON

{
  "id": "957bcbc6-1127-440f-b3d5-4da5b07f67b0",
  "name": "Community Contributed Multi-Agent Conversation",
  "nodes": 0,
  "category": "Community Templates",
  "status": "active",
  "version": "1.0.0"
}

Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.