Dynamic Multi-Agent AI Conversation Workflow
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This n8n workflow orchestrates dynamic conversations with multiple AI agents, intelligently routing user queries to the most relevant AI or engaging all agents in a contextual discussion. It maintains conversational memory and allows for highly personalized interactions based on global settings.
About This Workflow
Unleash the power of collaborative AI with this sophisticated n8n workflow. Designed for dynamic multi-agent conversations, it intelligently analyzes incoming chat messages to route queries to specific AI personalities (e.g., @SalesBot, @SupportAgent) using mentions. If no specific agent is addressed, the workflow engages all defined agents in a randomized order, fostering a collaborative AI environment. Each AI agent is equipped with a unique system message, configurable personality, and access to a shared conversational memory, ensuring contextually rich and personalized interactions. This makes it ideal for building advanced chatbots, virtual assistants, or intelligent automation tools that can adapt to diverse user needs.
Key Features
- Dynamic Agent Routing: Automatically directs user queries to specific AI agents using
@mentionsor intelligently engages all agents in a conversation if no specific mention is made. - Configurable AI Personalities: Define unique system messages, roles, and contexts for each AI agent, allowing for specialized expertise and tailored responses.
- Persistent Conversational Memory: Leverage a buffer window memory to ensure AI agents remember previous interactions, providing continuity and depth to conversations.
- Personalized User Context: Integrate global settings and user details (like name, location, notes) into the AI's system message for highly personalized and relevant responses.
- Flexible Agent Orchestration: Easily define and manage multiple AI assistants, choosing their models and specific instructions, all within a no-code/low-code environment.
How To Use
- Set up Chat Trigger: Configure the
When chat message receivednode to connect to your desired chat platform (e.g., Slack, Discord, custom webhook). - Define Agent Personalities: Create a
SetorCodenode (e.g., namedDefine Agent Settings) to store details for each AI agent, includingname,model, and asystemMessagethat defines its role and instructions. - Establish Global Context: Use another
SetorCodenode (e.g.,Define Global Settings) to provide global parameters like user information or overarching instructions that all agents should consider. - Configure Mentions Logic: In the
Extract mentionscode node, adjust thechatMessageNodeName,agentSetupNodeName, andchatTextPathvariables if your node names or input paths differ from the default. - Adjust Conversational Memory: Customize the
Simple Memorynode'scontextWindowLengthto control how much past conversation history the AI agents remember for ongoing interactions.
Apps Used
Workflow JSON
{
"id": "8f9b0ebf-7732-45ab-9b85-102301a45095",
"name": "Dynamic Multi-Agent AI Conversation Workflow",
"nodes": 27,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 8f9b0ebf-7732...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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