Save Costs In RAG Workflows using the Q&A Tool With Multiple Models

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Built by Niklas Hatje Niklas Hatje
Created on June 06, 2026

Description

This template shows how to use the Question and Answer tool to save costs in RAG use cases.

Who is this for?
This template is for everyone who wants to start giving knowledge to their Agents through RAG.

Requirements
Have a PDF with custom knowledge that you want to provide to your agent.

Setup
No setup required. Just hit Execute Workflow, upload your knowledge document and then start chatting.

How to customize this to your needs
Add custom instructions to your Agent by changing the prompts in it.
Add a different way to load in knowledge to your vector store, e.g. by looking at some Google Drive files or loading knowledge from a table.
Describe your data properly in the Q&A tool
Exchange the Simple Vector Store nodes with your own vector store tools ready for production.
Add a more sophisticated way to rank files found in the vector store.

For more information read our docs on RAG in n8n.

Nodes Used (6)

AI Agent
@n8n/n8n-nodes-langchain.agent
Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader
Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi
OpenAI Chat Model
@n8n/n8n-nodes-langchain.lmChatOpenAi
Simple Vector Store
@n8n/n8n-nodes-langchain.vectorStoreInMemory
Vector Store Question Answer Tool
@n8n/n8n-nodes-langchain.toolVectorStore