Implement intelligent message buffering for AI chats with Redis and GPT-4-mini
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 16 nodes and runs when a chat message arrives. Along the way it connects Redis, OpenAI Chat Model and Redis Chat Memory.
How it runs
Trigger: When a chat message arrives.
- store (Redis): push
- count (Redis): incr
- check_first_message (If): checks a condition and branches into true / false
- timestamp (Redis): set
- Wait: pauses before continuing
- get_timestamp (Redis): get
- check_delay (If): checks a condition and branches into true / false
- extract (Redis): pop
- get_message (Redis): get
- set_message (Redis): set
…plus 2 more steps. See the full node list below.
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 (8)
- If
n8n-nodes-base.if - Redis
n8n-nodes-base.redis - OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - No Operation, do nothing
n8n-nodes-base.noOp - AI Agent
@n8n/n8n-nodes-langchain.agent - Redis Chat Memory
@n8n/n8n-nodes-langchain.memoryRedisChat - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Wait
n8n-nodes-base.wait
From the author
This workflow solves a critical problem in AI chat implementations: handling multiple rapid messages naturally without creating processing bottlenecks. Unlike traditional approaches where every user waits in the same queue, our solution implements intelligent…