Local RAG Chatbot with Ollama & Qdrant for PDFs

Build a 100% local Retrieval Augmented Generation (RAG) chatbot in n8n that answers questions from uploaded PDF documents using Qdrant vector store and Ollama LLM.

This n8n workflow enables a fully self-hosted RAG chatbot that processes PDF files, stores document chunks in a Qdrant vector database, and uses Ollama (Llama 3.2) with embeddings (mxbai-embed-large) to retrieve relevant information and generate accurate responses. The pipeline splits into Data Ingestion (form-based PDF upload and vector insertion) and Chatbot interaction, ensuring semantic search for precise answers without external APIs. Key benefits include complete data privacy, zero ongoin
Platform
n8n
Category
Social Media
Price
$24.99
Creator
Felix Rahman

How to import this workflow into n8n

  1. 1Purchase or download the workflow to get the n8n workflow JSON file.
  2. 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
  3. 3Open each node marked with a credential warning and connect your own accounts and API keys.
  4. 4Run the workflow once manually to verify the data flow, then toggle it to Active.

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