Build a RAG agent with n8n, Qdrant & OpenAI

This template helps you to create an intelligent document assistant that can answer questions from uploaded files.

It shows a complete single-vector RAG (Retrieval-Augmented Generation) system that automatically processes documents, lets you chat with it in natural language and provides accurate, source-cited responses.

The workflow consists of two parts: the data loading pipeline and RAG AI Agent that answers your questions based on the uploaded documents.

To test tis workflow, you can use the following example files in a shared [Google Drive folder](https://drive.google.com/drive/u/2/folders/1BevhU5qdgNDFbK4D9oAYGeK0Dt5sEaxQ).

💡 Find more information on creating RAG AI agents in n8n [on the official page](https://n8n.io/rag/).

🔗Example files

The template uses the following example files in the Google Docs format:

1. German Data Protection law: Bundesdatenschutzgesetz (BDSG) 2. Computer Security Incident Handling Guide (NIST.SP.800-61r2) 3. Berkshire Hathaway letter to shareholders from 2024