AI Agents
AI SQL Agent Chat Querying a Postgres Database
5 nodes
43
4
Manual trigger
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Workflow Description
A chat-driven workflow where a Chat Trigger passes the user's chatInput to an AI Agent configured as an sqlAgent with a Postgres data source. An OpenAI Chat Model node supplies gpt-4 as the language model, enabling natural-language questions to be answered as SQL queries against the connected database.
How it works
- 1.Chat Trigger receives the user's message from the chat panel.
- 2.The message text (chatInput) is passed as the agent's input.
- 3.The AI Agent runs in sqlAgent mode with Postgres set as its data source.
- 4.The OpenAI Chat Model node (gpt-4) connects to the agent as its language model.
Use cases
- Ask which tables exist in a Postgres database via plain language.
- Let non-technical users explore database contents through chat.
Requirements
- A valid OpenAI API credential in n8n with access to gpt-4.
- A configured Postgres credential attached to the agent's data source.
- n8n instance with LangChain nodes (chat trigger, agent, LM) installed.
Setup and testing in n8n
- Open the workflow in n8n and click the chat button at the bottom of the canvas.
- Paste a question such as 'Which tables are available?'
- Verify the agent responds after OpenAI and Postgres connections resolve.
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
OpenAI
AI Agent
Chat Trigger
Details
Trigger
Manual trigger
Nodes
5
Apps
3
Views
43
Downloads
4
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (5)
OpenAI Chat Model
OpenAI
AI Agent
Agent
Chat Trigger
Chat Trigger
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Source and license
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