AI Chatbot that Queries Baserow Database with OpenAI GPT-4 Mini

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Built by Gegenfeld Gegenfeld
Created on June 07, 2026

Description

This workflow creates an intelligent chatbot that uses your Baserow database as a knowledge base. The AI agent can automatically query your Baserow tables to provide accurate, contextual responses based on your stored data.

Who's it for

This template is perfect for:
Support teams using Baserow for knowledge management
Small businesses managing customer data in Baserow
Teams looking for an open-source alternative to Airtable-based chatbots
Organizations that want to make their Baserow data conversationally accessible
Self-hosted solution enthusiasts who prefer controlling their data

How it works

The workflow combines OpenAI's language model with Baserow's open-source database capabilities to create a smart chatbot. When users ask questions, the AI agent automatically determines which Baserow records are relevant and uses that data to generate helpful responses. The system maintains conversation history for natural, contextual interactions.

How to set up

Add your credentials:
Configure your Baserow API credentials in the Baserow Database node
Set up your OpenAI API credentials in the OpenAI Chat Model node

Configure your Baserow connection:
Click the Baserow Database node
Select your Baserow table containing your knowledge base data
The AI will automatically determine relevant records - no need to specify individual record IDs

Customize the AI model:
Open the OpenAI Chat Model node
Choose your preferred model (GPT-4, GPT-3.5-turbo, etc.)
Adjust token limits if needed

Test the chatbot:
Click the Chat button to start a conversation
Ask questions related to your Baserow data

Optional - Make it public:
Enable public access in the Chat Trigger node
Embed the provided code into your website

Requirements

n8n instance (cloud or self-hosted)
Baserow instance (self-hosted or cloud) with data you want to query
OpenAI API key with available credits
Baserow API token with appropriate permissions

How to customize the workflow

Change the AI Provider:
You can replace the OpenAI Chat Model with other providers like Anthropic Claude, Google Gemini, or local models by swapping the language model node.

Adjust Context Window:
Modify the "Remember Chat History" node to increase or decrease how many previous messages the AI remembers (default is 10 interactions).

Update System Instructions:
Edit the Smart AI Agent's system message to change how the assistant behaves or add specific instructions for your use case.

Connect Multiple Tables:
Add additional Baserow Database nodes to give the AI access to multiple tables within your Baserow workspace.

Add More Tools:
Extend the AI agent with additional tools like web search, email sending, or integration with other services.

Workflow Structure

Chat Trigger → Smart AI Agent ← OpenAI Chat Model

Baserow Database

Remember Chat History

The Smart AI Agent orchestrates the conversation, deciding when to query Baserow and how to use the retrieved data in responses. The memory buffer ensures natural conversation flow by maintaining context across interactions.

Nodes Used (3)

AI Agent
@n8n/n8n-nodes-langchain.agent
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Simple Memory
@n8n/n8n-nodes-langchain.memoryBufferWindow