Local Chatbot with Retrieval Augmented Generation (RAG)

n8n template #5148

Summary

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

How to set it up

Open template #5148 on n8n.io and click Use for free, or copy the template JSON and paste it onto an empty canvas in n8n.
Create 3 credentials under Credentials → Add credential: Ollama Chat Model, Qdrant Vector Store, Embeddings Ollama. Then open each of those nodes and pick the credential.
Check the model in the AI Agent node. The template may point at a model your account can't use; swap it for one you have access to.
Click Execute workflow and step through each node's output to confirm the data looks right.
Toggle the workflow to Active so its trigger runs on its own.

Hand off to your agent

Prompt

Help me set up the n8n workflow "Local Chatbot with Retrieval Augmented Generation (RAG)" (https://n8n.io/workflows/5148). It uses: AI Agent, Ollama Chat Model, Simple Memory, Recursive Character Text Splitter, Default Data Loader, Qdrant Vector Store, Embeddings Ollama. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.

Paste into Claude Code and it will do the rest.

Apps and nodes

AI Agent Ollama Chat Model Simple Memory Recursive Character Text Splitter Default Data Loader Qdrant Vector StoreEmbeddings Ollama

Questions

Yes. Thomas Janssen published it free on n8n.io as a verified creator, and it has 29K views. It runs on n8n Cloud or a self-hosted n8n instance.

Ollama Chat Model, Qdrant Vector Store, Embeddings Ollama. The other 4 nodes are built into n8n.

Similar workflows

NameViews