Local Chatbot with Retrieval Augmented Generation (RAG)
Build a 100% local RAG with n8n, Ollama and Qdrant. This agent uses a semantic database (Qdrant) to answer questions ab…
Description
Build a 100% local RAG with n8n, Ollama and Qdrant. This agent uses a semantic database (Qdrant) to answer questions about PDF files. Tutorial Click here to view the YouTube Tutorial How it works Build a chatbot that answers based on documents you provide it (Retrieval Augmented Generation). You can upload as many PDF files as you want to the Qdrant database. The chatbot will use its retrieval tool to fetch the chunks and use them to answer questions. Installation Install n8n + Ollama + Qdrant using the Self-hosted AI starter kit Make sure to install Llama 3.2 and mxbai-embed-large as embeddings model. How to use it First run the "Data Ingestion" part and upload as many PDF files as you want Run the Chatbot and start asking questions about the documents you uploaded. An n8n automation workflow template by Thomas Janssen.
Community Metrics
Author
Thomas Janssen
Platform
web
Pricing model
free
Categories
- Automation
- AI
Tags
- n8n
- workflow
- ai-agent
- ollama-chat-model
- simple-memory
- recursive-character-text-splitter
- default-data-loader
- qdrant-vector-store
- embeddings-ollama
Capabilities
- 7 nodes
- 28,717 views