Chat with PDF / MD / text files using GraphRAG (no vector store needed)

Set up a chat with your documents without the complex vector store setup. This templates helps you - ingest your PDF / text / MD documents into a knowledge graph - use the graph as the knowledge base for your AI chatbots (and other workflows) - visualize the main topics and gaps in your documents (good for observability and research) The knowledge base is provided using the InfraNodus GraphRAG with the knowledge graphs offering high-quality responses without the need to set up complex RAG vector store workflows. The advantages of using GraphRAG instead of the standard vector stores for knowledge are: - Easy and quick to set up and update — no complex data import workflows needed - A knowledge graph offers a holistic and interactive view of your knowledge base (accessible via our API or a web interface — also shareable) - Better retrieval of relations between the document chunks = higher quality responses !InfraNodus knowledge graph How it works This template uses the InfraNodus knowledge graph as a knowledge base for your n8n AI agent node. The knowledge graph contains the documents you can upload using this template from your Google Drive. When the user asks a question via the chat interface, the agent forwards this question to the InfraNodus knowledge graph, retrieves a response, a summary, and a list of matching statements (based advanced Graph RAG), then delivers the final response back the user. Here's a description step by step: Step 1: Upload your documents - Put the PDF / text / MD files you want to chat with into a folder on your Google drive - Authorize access to that folder using the Google drive node in the template. - Add the InfraNodus API key to the InfraNodus Save to Graph HTTP node - Optional: change the name of the graph you want to save the data to in the InfraNodus HTTP node (in the name field of the HTTP post request). - Run the workflow to ingest all the files and save them into the graph - Optional: check the link provided in the Step 1 workflow description to see the visualization of your knowledge base. It will look something like that: !InfraNodus graph knowledge base Note: you can replace the PDF to Text convertor node with a better quality PDF convertor from ConvertAPI which respects the original file layout and doesn't split text into small chunks Step 2: Chat with your documents - Deactive the trigger in the Step 1 - Activate the chat trigger in the Step 2 - Add your InfraNodus API credentials to Knowledge Base GraphRAG InfraNodus node - Optional: change the graph name in the Knowledge Base node to match the name you provided in the step 1 above - Run the chat and ask the question - Watch the magic How to use You need an InfraNodus GraphRAG API account and key to use this workflow. - Create an InfraNodus account - Get the API key at https://infranodus.com/api-access and create a Bearer authorization key for the InfraNodus HTTP nodes. Requirements - An InfraNodus account and API key - An OpenAI (or any other LLM) API key - A Google Drive OAuth access (follow the n8n instructions) - Optional: ConvertAPI API key for better quality PDF conversion Customizing this workflow You can customize this workflow by adding several experts to your AI agent. Check out the complete guide at https://support.noduslabs.com/hc/en-us/articles/20174217658396-Using-InfraNodus-Knowledge-Graphs-as-Experts-for-AI-Chatbot-Agents-in-n8n Also check out the video tutorial with a demo: !Video tutorial For support and feedback, please, contact us at https://support.noduslabs.com To learn more about InfraNodus: https://infranodus.com