Local File to RAG QA Chatbot with Mistral AI

Overview

This n8n workflow transforms a local folder of documents into a queryable AI knowledge base. It leverages the Local File Trigger to detect new or modified files. The Set Variables node extracts file information and sets up parameters for Qdrant. Files are then read, prepared for embedding with their content, location, and timestamp using Prepare Embedding Document. Embeddings Mistral Cloud generates vector embeddings, and Default Data Loader along with Recursive Character Text Splitter prepares these for a vector store. The workflow integrates with Qdrant (though the provided snippet is incomplete for the Qdrant interaction itself, it implies storage). Crucially, it sets up a Chat Trigger and Question and Answer Chain powered by Mistral AI's Mistral Cloud Chat Model and a Vector Store Retriever, enabling users to ask questions about the processed documents.