Build an On-Premises AI Kaggle Competition Assistant with Qdrant RAG and Ollama
LLM/RAG Kaggle Development Assistant An on-premises, domain-specific AI assistant for Kaggle (tested on binary disaster-tweet classification), combining LLM, an n8n workflow engine, and…
- Use case
- Engineering
- Difficulty
- advanced
- Author
- JHH
- Updated
- Jun 7, 2026
Required custom nodes
- switch
- localFileTrigger
- markdown
- agent
- chainSummarization
- lmChatOllama
- lmOllama
- memoryBufferWindow
Build an On-Premises AI Kaggle Competition Assistant with Qdrant RAG and Ollama
A working n8n automation that runs against a local model via Ollama - 2,052 views on the n8n template library. LLM/RAG Kaggle Development Assistant An on-premises, domain-specific AI assistant for Kaggle (tested on binary disaster-tweet classification), combining LLM, an n8n workflow engine, and…
What it does
LLM/RAG Kaggle Development Assistant An on-premises, domain-specific AI assistant for Kaggle (tested on binary disaster-tweet classification), combining LLM, an n8n workflow engine, and… It chains 19 nodes, integrating switch, localFileTrigger, markdown, agent.
Requirements
- n8n (self-hosted, free) to run the workflow
- Ollama serving a local model
- 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
Workflow by JHH on the n8n template library. We link to the original to import; credit and the workflow JSON belong to its author.