Save Costs in RAG Workflows with Q&A Tool & Multiple Models

This workflow enables cost-efficient RAG by uploading knowledge files via a form, embedding them with OpenAI, and using a Q&A tool for agent queries without full reprocessing.

This n8n workflow demonstrates a smart approach to implementing Retrieval-Augmented Generation (RAG) while minimizing costs. It starts with a Form Trigger node where users upload PDF or CSV files containing custom knowledge. These files are then processed through OpenAI Embeddings to create vector representations, stored in a Simple Vector Store for quick retrieval. The core innovation is the Question and Answer (Q&A) Tool, which allows agents to query the vector store efficiently. Instead of r
Platform
n8n
Category
Surveys & Forms
Price
$14.99
Creator
Jonas Sato

How to import this workflow into n8n

  1. 1Purchase or download the workflow to get the n8n workflow JSON file.
  2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
  3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
  4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

Related Surveys & Forms workflows

More from Jonas Sato

Need this deployed? We'll set it up for you.

Our automation experts deploy this workflow in your stack, connect your accounts, and verify it works — or build a custom solution from scratch.