Build your first RAG AI agent with n8n and learn the basics of RAG (Retrieval Augumented Generation). In this tutorial, we'll be building a simple RAG Agent that lets you chat with your documents. For this, we'll be using Pinecone as our vector database and Mistral for both the embeddings and chat functionality. As both services offer a free tier, you'll be able to following along and build this agent without any cost at all.
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TIMESTAMPS
00:00 Intro
00:47 Start building the data insertion feature
02:37 Create Pinecone vectore database
05:28 Setup data loader and text splitter
08:00 Insert document into Pinecone vector storage
12:39 Testing out the system
14:09 Simple explanation of RAG
16:42 Outro