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Multi-Agent Conversation

18 nodes · chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter

Engine
n8n
Nodes
18
Trigger
scheduled/triggered
Source file
1926_Stickynote_Splitinbatches_Automation_Triggered.json

Workflow flow

IntegrationsChatAgentSplitInBatchesMemoryBufferWindowLmChatOpenRouter@n8n/n8n-nodes-langchain.chat@n8n/n8n-nodes-langchain.agentCode@n8n/n8n-nodes-langchain.memoryBufferWindowSetIF@n8n/n8n-nodes-langchain.lmChatOpenRouter
100%
TRIGGER

When chat message received

@n8n/n8n-nodes-langchain.chat

Simple Memory

@n8n/n8n-nodes-langchain.memoryBufferWindow

OpenRouter Chat Model

@n8n/n8n-nodes-langchain.lmChatOpenRouter

Define Global Settings

Code

Define Agent Settings

Code

Extract mentions

Code

Set lastAssistantMessage

Set

Loop Over Items

SplitInBatches

First loop?

IF

Combine and format responses

Code

Set last Assistant message as input

Set

Set user message as input

Set

AI Agent

@n8n/n8n-nodes-langchain.agent

13 steps · flows top to bottom, branches left to right

Browse by integration

chatagentsplitInBatchesmemoryBufferWindowlmChatOpenRouter
Browse all integrations →
Download n8n JSONDownload sanitized JSONDownload flow graph

Import into n8n

  1. Download the n8n JSON file (full or sanitized).
  2. In n8n: Workflows → Import from file.
  3. Open each node and reconnect credentials to your accounts.
  4. Test with manual execution before enabling triggers.

Sanitized JSON removes credential IDs — safer for sharing. Flow graph JSON is OpenRuna's lightweight format for diagrams and other tools, not n8n import.

View source corpus ↗

Overview

Free n8n workflow: Multi-Agent Conversation. 18 nodes across chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter, with a downloadable JSON and a visual flow diagram on OpenRuna.

What this workflow does

"Multi-Agent Conversation" is an n8n automation built from 18 nodes spanning chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter. 18 nodes · chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter A scheduled/triggered entry point kicks it off, and each node passes data to the next until the run completes. On OpenRuna you get the visual graph, the integration list, and a downloadable JSON ready to import into n8n. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

  • Use it as a starting template when wiring chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter — adjust node parameters to your accounts and record IDs.
  • Import "Multi-Agent Conversation" into n8n, reconnect credentials for chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter, and run the same automation in your own workspace.
  • Share it with your team as a documented reference for scheduled/triggered automations in the chat stack.
  • Study how data moves from chat to agent before building your own variant.

Example output

Imported into n8n, "Multi-Agent Conversation" exposes 18 configured nodes. Trigger type: scheduled/triggered. Integrations: chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter. Open each node after import to map credentials to your own chat and agent accounts. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Paste the exported JSON for "Multi-Agent Conversation" into Claude and ask it to explain each of the 18 nodes. Claude is good at suggesting credential mappings for chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter, plus error-handling and idempotency improvements before you run it in production.

ChatGPT

Have ChatGPT generate a checklist for adapting "Multi-Agent Conversation" to your accounts — which chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter credentials to create and which node parameters to change first.

Cursor

Open the downloaded JSON in Cursor and use Agent mode to refactor hard-coded URLs into env vars, or to generate tests for any Code nodes. Keep the OpenRuna flow diagram open so you do not break connection order across the 18 nodes.

Frequently asked questions

How do I import "Multi-Agent Conversation" into n8n?
Click Download n8n JSON on this page, then in n8n choose Workflows → Import from file and select the downloaded file. Reconnect credentials on each node — the export carries credential IDs from the original author's instance, not working secrets.
Which integrations does "Multi-Agent Conversation" use?
It uses: chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter. The flow diagram above shows how each service connects across the 18 nodes. Filter OpenRuna by integration to find related workflows and tools.
Can I import a sanitized export without credentials?
Yes. Use "Download sanitized JSON" to strip credential references before sharing internally. You will still add your own chat and agent credentials in n8n after import.
What trigger type does "Multi-Agent Conversation" use?
Trigger type: scheduled/triggered. After import, confirm the trigger node (webhook, schedule, or app event) matches your environment, then activate the workflow when you are ready to run it.
Is "Multi-Agent Conversation" free to use?
OpenRuna catalogs community n8n workflows under open licenses. Check the source corpus link for the original license; commercial use may require verifying the third-party API terms for chat, agent, splitInBatches, memoryBufferWindow, lmChatOpenRouter.

Related resources