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
- RAG
- Chatbot
- Ollama
- Qdrant
- Vector Store
- PDF Processing
- Local AI
- Self-Hosted AI
- Document Q&A
- n8n AI
How to import this workflow into n8n
- 1Purchase or download the workflow to get the n8n workflow JSON file.
- 2In your n8n instance, open Workflows and choose "Import from File" (or paste the JSON with Ctrl+V on the canvas).
- 3Open each node marked with a credential warning and connect your own accounts and API keys.
- 4Run the workflow once manually to verify the data flow, then toggle it to Active.
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