Build a Document-based AI Chatbot with Google Drive, Llama 3, and Qdrant RAG
Overview This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By…
- Use case
- Internal Wiki
- Difficulty
- intermediate
- Author
- Mohsin
- Updated
- Jun 7, 2026
Required models
Required custom nodes
- googleDrive
- googleDriveTrigger
- agent
- lmChatOllama
- textSplitterRecursiveCharacterTextSplitter
- documentDefaultDataLoader
- chatTrigger
- vectorStoreQdrant
Build a Document-based AI Chatbot with Google Drive, Llama 3, and Qdrant RAG
A working n8n automation that runs against a local model via Ollama - 271 views on the n8n template library. Overview This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By…
What it does
Overview This template allows users to set up an AI-powered chatbot that retrieves and processes knowledge from Google Drive documents using Retrieval-Augmented Generation (RAG). By… It chains 10 nodes, integrating googleDrive, googleDriveTrigger, agent, lmChatOllama.
Requirements
- n8n (self-hosted, free) to run the workflow
- Ollama serving a local model such as llama3-1-8b
- A GPU with enough VRAM for your chosen model (see best model per GPU)
Import it
Open the workflow on the n8n template library and click Use workflow to import it into your self-hosted n8n, then point its model node at your local Ollama endpoint (http://localhost:11434).
Use it with
n8n · Ollama · llama3-1-8b
Workflow by Mohsin on the n8n template library. We link to the original to import; credit and the workflow JSON belong to its author.