⚒️ Visualize your SQL Agent queries with OpenAI and Quickchart.io

⚡ 16,437 views · ⚒️ Engineering

Description

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 capabilities thanks to OpenAI’s Structured Output and Quickchart.io.

How it works

1. Information Extraction:

   • The Information Extractor identifies and extracts the user’s question.
   • If the question includes a visualization aspect, the SQL Agent alone may not respond accurately.

2. SQL Querying:

   • It leverages a regular SQL Agent: it connects to a database, queries it, and translates the response into a human-readable format.

3. Chart Decision:

   • The Text Classifier determines whether the user would benefit from a chart to support the SQL Agent’s response.

4. Chart Generation:

   • If a chart is needed, the sub-workflow dynamically generates a chart and appends it to the SQL Agent’s response.
   • If not, the SQL Agent’s response is output as is.

5. Calling OpenAI for Chart Definition:

   • The sub-workflow calls OpenAI via the HTTP Request node to retrieve a chart definition.

6. Building and Returning the Chart:

   • In the “Set Response” node, the chart definition is appended to a Quickchart.io URL, generating the final chart image.
   • The AI Agent returns the response along with the chart.

How to use it

• Use an existing database or create a new one.
• For example, I’ve used this Kaggle dataset and uploaded it to a Supabase DB.
• Add the PostgreSQL or MySQL credentials.
• Alternatively, you can use SQLite binary files (check this template).
• Activate the workflow.
• Start chatting with the AI SQL Agent.
• If the Text Classifier determines a chart would be useful, it will generate one in addition to the SQL Agent’s response.

Notes

• The full Quickchart.io specifications have not been fully integrated, so there may be some glitches (e.g., radar graphs may not display properly due to size limitations).

🔗 Nodes Used

HTTP Request, Execute Sub-workflow, Execute Workflow Trigger, AI Agent, OpenAI Chat Model, Simple Memory

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup