I Built a RAG Chatbot AI Agent with n8n (No Code, Step-by-Step Tutorial)
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In this video, I'll show you how to build a beginner-friendly Q&A AI agent in n8n that can search through large PDF documents and have conversations with you about their content.
Most people think working with large documents in AI requires complex coding, but I've created a no-code solution that handles everything automatically.
What you'll learn:
Connect n8n to Google Drive to access your PDF documents
Set up Pinecone as a vector database to store and search large files
Create a conversational AI agent that can answer questions about your documents
Store your conversation history in Airtable for future reference
Process hundreds of pages of content with semantic search capabilities
I'll walk you through the full process, from setting up your Google Drive connection to building the complete workflow in n8n.
You'll see a real-time demo where the automation takes multiple large PDF books (Alex Hormozi's books), chunks the content, and creates an AI assistant that can answer specific questions and cite exactly where the information came from—all through a simple chat interface.
This is perfect for researchers, content creators, or anyone who needs to quickly extract information from large documents. I'll guide you through it step by step, showing you exactly how to implement this powerful tool for your own use case.
Chapters
00:00 - Introduction to Building a Q&A AI Agent
00:20 - Setting Up the Example with PDF Books
02:11 - Game Plan and Workflow Setup in N8N
02:31 - Preparing and Uploading Documents to Pinecone
03:23 - Search and Retrieve Process with Pinecone
03:43 - Storing Conversations in Airtable
04:05 - Building the Workflow in N8N Part 1
07:04 - Advanced Configuration and Testing with Pinecone
13:09 - Setting Up the AI Agent for Q&A
14:52 - Finalizing the AI Agent and Airtable Integration