Tutor English chat messages using OpenRouter with Postgres memory and log to Supabase
Ready for 3.0Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 7 nodes and runs when an HTTP POST request hits its webhook URL. Along the way it connects OpenRouter Chat Model, Postgres Chat Memory and Supabase.
How it runs
Trigger: When an HTTP POST request hits its webhook URL.
- Edit Fields (Edit Fields (Set)): sets 2 fields: user_id, message
- AI Agent: runs an AI agent, with model: OpenRouter Chat Model; memory: Postgres Chat Memory
- Log to Supabase (Supabase): uses Supabase
- Respond to Webhook: sends the response back to the webhook caller
Services it uses
Before you upgrade to n8n 3.0
Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.
Nodes used (7)
- Webhook
n8n-nodes-base.webhook - Respond to Webhook
n8n-nodes-base.respondToWebhook - Edit Fields (Set)
n8n-nodes-base.set - AI Agent
@n8n/n8n-nodes-langchain.agent - OpenRouter Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenRouter - Postgres Chat Memory
@n8n/n8n-nodes-langchain.memoryPostgresChat - Supabase
n8n-nodes-base.supabase
From the author
Quick overview This workflow receives English practice messages via a webhook, uses an OpenRouter chat model with Postgres-backed conversation memory to generate tutoring feedback, logs the exchange to Supabase, and returns the tutor’s reply as a JSON…