Chat with a database using AI

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

This workflow allows you to ask questions about data stored in a database using AI. To use it, you'll need an OpenAI API key (although you could also swap in a model from another service). Supporte...

Best for

Internal Wiki automation workflows
AI RAG automation workflows
intermediate n8n builders looking for reusable templates

Tools used

n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.chattrigger, n8n-nodes-base.postgrestool, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by David Roberts.

Original n8n.io source

1.1 Workflow description

Title: Chat with a database using AI
Workflow name: Chat with a database using AI

This workflow allows you to ask questions about data stored in a database using AI.

To use it, you'll need an OpenAI API key (although you could also swap in a model from another service).

Supported databases:

Postgres
MySQL
SQLite

The workflow uses n8n's embedded chat, but you could also modify it to work with a chat service such as Slack, MS Teams or WhatsApp.

Note that to use this template, you need to be on n8n version 1.19.4 or later.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 2 - Sticky Note1

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 3 - When chat message received

Type / Role: @n8n/n8n-nodes-langchain.chatTrigger - chatTrigger
Config choices: Version 1.1

Block 4 - Postgres

Type / Role: n8n-nodes-base.postgresTool - postgresTool
Config choices: Version 2.5

Block 5 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 6 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.8

Block 7 - OpenAI Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices: Version 1.2

3. Summary Table

Workflow	Chat with a database using AI
Complexity	intermediate
Nodes	7
Categories	Internal Wiki, AI RAG
Author	David Roberts
Published	13 Feb 2024

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/2090/2090.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Internal Wiki workflows AI RAG workflows

Frequently asked questions

What does Chat with a database using AI do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Internal Wiki, AI RAG use case.

David Roberts

18 workflows

Nodes

n8n-nodes-base.stickynote @n8n/n8n-nodes-langchain.chattrigger n8n-nodes-base.postgrestool @n8n/n8n-nodes-langchain.memorybufferwindow @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai

Complexity

intermediate

Published 13 Feb 2024

Likes 0

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Install path: /data/workflows/2090/2090.json

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Chat with a database using AI

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Sticky Note

Block 2 - Sticky Note1

Block 3 - When chat message received

Block 4 - Postgres

Block 5 - Simple Memory

Block 6 - AI Agent

Block 7 - OpenAI Chat Model

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions