Talk to your SQLite database with a LangChain AI Agent 🧠💬

n8n template #2292

Summary

This n8n workflow demonstrates how to create an agent using LangChain and SQLite. The agent can understand natural language queries and interact with a SQLite database to provide accurate answers. 💪 🚀 Setup Run the top part of the workflow once. It downloads the example SQLite database, extracts from a ZIP file and saves locally (chinook.db). 🗣️ Chatting with Your Data Send a message in a chat window. Locally saved SQLite database loads automatically. User's chat input is combined with the binary data. The LangChain Agend node gets both data and begins to work. The AI Agent will process the user's message, perform necessary SQL queries, and generate a response based on the database inform

How to set it up

Open template #2292 on n8n.io and click Use for free, or copy the template JSON and paste it onto an empty canvas in n8n.
Create a credential under Credentials → Add credential: OpenAI Chat Model. Then open each of those nodes and pick the credential.
Check the model in the AI Agent node. The template may point at a model your account can't use; swap it for one you have access to.
Click Execute workflow and step through each node's output to confirm the data looks right.
Toggle the workflow to Active so its trigger runs on its own.

Hand off to your agent

Prompt

Help me set up the n8n workflow "Talk to your SQLite database with a LangChain AI Agent 🧠💬" (https://n8n.io/workflows/2292). It uses: HTTP Request, Compression, AI Agent, OpenAI Chat Model, Simple Memory. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.

Paste into Claude Code and it will do the rest.

Apps and nodes

HTTP RequestCompressionAI Agent OpenAI Chat Model Simple Memory

Questions

Yes. Yulia published it free on n8n.io as a verified creator, and it has 22K views. It runs on n8n Cloud or a self-hosted n8n instance.

OpenAI Chat Model. The other 4 nodes are built into n8n.

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