Visualize your SQL Agent queries with OpenAI and Quickchart.io
Needs changesNeeds changes. This template uses 1 thing(s) that n8n 3.0 removes: AI Agent v1 (old agent modes). 1 breaking item(s) found. Static check, last run 2026-10-19.
What this workflow does
This AI workflow has 14 nodes and runs when a chat message arrives (plus 1 other trigger). Along the way it connects OpenAI Chat Model. It also calls api.openai.com over HTTP.
How it runs
Trigger: When a chat message arrives (plus 1 other trigger).
- Information Extractor: extracts structured fields from text with AI, with model: OpenAI Chat Model
- OpenAI - Generate Chart definition with Structured Output (HTTP Request): calls api.openai.com (POST)
- AI Agent: runs an AI agent, with model: OpenAI Chat Model; memory: Window Buffer Memory
- Set response (Edit Fields (Set)): sets 1 field: output
- Text Classifier: classifies text into categories with AI, with model: OpenAI Chat Model
- User question + Agent initial response (Edit Fields (Set)): sets 2 fields: user_question, output
- Set Text output (Edit Fields (Set)): sets 1 field: output
- Execute Workflow (Execute Sub-workflow): calls another n8n workflow
- Set Text + Chart output (Edit Fields (Set)): sets 1 field: output
Services it uses
HTTP calls to: api.openai.com
Before you upgrade to n8n 3.0
1 thing in this workflow is removed in n8n 3.0. Fix it before you upgrade:
- AI Agent v1 (old agent modes) in AI Agent (v1.7): replace with Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent.
| Removed in 3.0 | Replace with |
|---|---|
| AI Agent v1 (old agent modes) AI Agent (v1.7) | Latest AI Agent node (Tools Agent). For SQL Agent, use a Postgres or MySQL tool with a recent AI Agent. |
Nodes used (10)
- OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi - Execute Sub-workflow
n8n-nodes-base.executeWorkflow - Execute Workflow Trigger
n8n-nodes-base.executeWorkflowTrigger - HTTP Request
n8n-nodes-base.httpRequest - Edit Fields (Set)
n8n-nodes-base.set - Chat Trigger
@n8n/n8n-nodes-langchain.chatTrigger - AI Agent
@n8n/n8n-nodes-langchain.agent - Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow - Text Classifier
@n8n/n8n-nodes-langchain.textClassifier - Information Extractor
@n8n/n8n-nodes-langchain.informationExtractor
From the author
Overview - This workflow aims to provide data visualization capabilities to a native SQL Agent. - Together, they can help foster data analysis and data visualization within a team. - It uses the native SQL Agent that works well and adds visualization…