N8N Documentation Expert Chatbot with OpenAI RAG Pipeline

How It Works

This template is a complete, hands-on tutorial for building a RAG (Retrieval-Augmented Generation) pipeline. In simple terms, you'll teach an AI to become an expert on a specific topic—in this case, the official n8n documentation—and then build a chatbot to ask it questions.

Think of it like this: instead of a general-knowledge AI, you're building an expert librarian.

🔧 Workflow Overview

The workflow is split into two main parts:

Part 1: Indexing the Knowledge (📚 Building the Library)

This is a one-time process you run manually. The workflow will:

Automatically scrape all pages of the n8n documentation. Break them down into small, digestible chunks. Use an AI model to create a numerical representation (an embedding) for each chunk. Store these embeddings in n8n's built-in Simple Vector Store.