Generate AI prompts with Google Gemini and store them in Airtable
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 11 nodes and runs when a chat message arrives. Along the way it connects Google Gemini Chat Model and Airtable.
How it runs
Trigger: When a chat message arrives.
- Generate a new prompt (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model
- Edit Fields (Edit Fields (Set)): sets 1 field: text
- Categorize and name Prompt (Basic LLM Chain): sends a prompt to an LLM, with model: Google Gemini Chat Model; output parser: Auto-fixing Output Parser
- set prompt fields (Edit Fields (Set)): sets 3 fields: name, category, Prompt
- add to airtable (Airtable): create
- Return results (Edit Fields (Set)): sets 1 field: text
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)
- Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini - Auto-fixing Output Parser
@n8n/n8n-nodes-langchain.outputParserAutofixing - Structured Output Parser
@n8n/n8n-nodes-langchain.outputParserStructured - Edit Fields (Set)
n8n-nodes-base.set - Basic LLM Chain
@n8n/n8n-nodes-langchain.chainLlm - Airtable
n8n-nodes-base.airtable
From the author
This workflow is designed to generate prompts for AI agents and store them in Airtable. It starts by receiving a chat message, processes it to create a structured prompt, categorizes the prompt, and finally stores it in Airtable. 2. Setup Instructions…