Date: 04/28/2025
Alright, so this video is all about leveling up your RAG (Retrieval-Augmented Generation) pipelines in n8n to handle more than just plain text. It tackles the common problem of dealing with different file types like PDFs and Excel sheets when building your knowledge base. The creator walks you through a workflow to extract text from these files, which n8n doesn’t natively support with a single node.
This is super valuable for anyone like me diving into AI-enhanced workflows. One of the biggest hurdles I’ve faced is getting data into the system. We often have project requirements where the knowledge base isn’t just text files; it’s documentation, spreadsheets, PDFs, even scanned images. This video shows a practical, no-code/low-code approach to ingest those diverse file types, clean and transform them for use in LLMs. The link to the workflow and the Google MIME types are clutch!
Imagine automating document processing for a client, extracting key data from reports or contracts, and feeding it into your LLM-powered chatbot or analysis tool. No more manual copy-pasting! The video’s approach of breaking down the extraction process and handling different file types really resonated with me. I am downloading this workflow right now and planning on applying a similar approach to process and extract information from scanned images using OCR and then load it into a vector database. Worth experimenting with? Absolutely! It’s about bridging the gap between raw data and intelligent applications, making our AI agents more versatile and effective.