How do I import "Use any LLM-Model via OpenRouter" 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 "Use any LLM-Model via OpenRouter" use?

It uses: chat, agent, memoryBufferWindow, lmChatOpenAi. The flow diagram above shows how each service connects across the 8 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 "Use any LLM-Model via OpenRouter" 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 "Use any LLM-Model via OpenRouter" 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, memoryBufferWindow, lmChatOpenAi.

← Workflows

Use any LLM-Model via OpenRouter

8 nodes · chat, agent, memoryBufferWindow, lmChatOpenAi

Engine: n8n
Nodes: 8
Trigger: scheduled/triggered
Source file: 1734_Stickynote_Automation_Triggered.json

Workflow flow

IntegrationsChatAgentMemoryBufferWindowLmChatOpenAiSet@n8n/n8n-nodes-langchain.chat@n8n/n8n-nodes-langchain.agent@n8n/n8n-nodes-langchain.memoryBufferWindow@n8n/n8n-nodes-langchain.lmChatOpenAi

100%

TRIGGER

When chat message received

@n8n/n8n-nodes-langchain.chat

Chat Memory

@n8n/n8n-nodes-langchain.memoryBufferWindow

LLM Model

@n8n/n8n-nodes-langchain.lmChatOpenAi

Settings

Set

AI Agent

@n8n/n8n-nodes-langchain.agent

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

Browse by integration

chat agent memoryBufferWindow lmChatOpenAi

Browse all integrations →

Download n8n JSON Download sanitized JSON Download flow graph

Import into n8n

Download the n8n JSON file (full or sanitized).
In n8n: Workflows → Import from file.
Open each node and reconnect credentials to your accounts.
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

Use any LLM-Model via OpenRouter (8-node n8n automation, chat, agent, memoryBufferWindow, lmChatOpenAi) is free on OpenRuna — view the graph and export the JSON to import into n8n.

What this workflow does

Built in n8n, "Use any LLM-Model via OpenRouter" chains 8 nodes to move data between chat, agent, memoryBufferWindow, lmChatOpenAi. 8 nodes · chat, agent, memoryBufferWindow, lmChatOpenAi Execution begins at the scheduled/triggered trigger and flows through the 8 configured nodes. OpenRuna renders the node graph and offers the JSON export so you can import and adapt it in minutes. Use it to learn integration patterns, fork it for your own use case, or deploy it quickly after reconnecting credentials.

Use cases

Fork it to add error handling, retries, or a notification step without designing the 8-node flow from scratch.
Benchmark it against your current chat integration to spot missing steps or redundant nodes.
Study how data moves from chat to agent before building your own variant.
Share it with your team as a documented reference for scheduled/triggered automations in the chat stack.

Example output

Imported into n8n, "Use any LLM-Model via OpenRouter" exposes 8 configured nodes. Trigger type: scheduled/triggered. Integrations: chat, agent, memoryBufferWindow, lmChatOpenAi. Reconnect the chat credential first, then walk the remaining nodes top to bottom. Run it once in test mode to verify any branch logic (Switch/IF nodes) before enabling production triggers.

Tips by platform

Claude

Ask Claude to turn the "Use any LLM-Model via OpenRouter" JSON into a plain-English runbook, node by node. It can flag where chat rate limits or missing retries might bite before you go live.

ChatGPT

Drop the workflow JSON or this OpenRuna page URL into ChatGPT and ask for a step-by-step runbook: triggers, branches, and which fields to customise for chat, agent, memoryBufferWindow, lmChatOpenAi. Handy for onboarding teammates new to n8n.

Cursor

In Cursor, ask Agent mode to parameterise "Use any LLM-Model via OpenRouter" — extract chat IDs and secrets into environment variables without changing the 8-node structure.

Frequently asked questions

How do I import "Use any LLM-Model via OpenRouter" 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 "Use any LLM-Model via OpenRouter" use?: It uses: chat, agent, memoryBufferWindow, lmChatOpenAi. The flow diagram above shows how each service connects across the 8 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 "Use any LLM-Model via OpenRouter" 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 "Use any LLM-Model via OpenRouter" 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, memoryBufferWindow, lmChatOpenAi.