n8n21 modulesv1.0LLM/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 Qdrant-backed Retrieval-Augmented Generation (RAG). Deploy via containerized starter kit. Needs high end GPU support or patience. Initial chat should contain guidelines on what to to produce and the challenge guidelines. --- Features - Coding Assistance • "Real"-time Python code recommendations, debugging help,
Build an on-premises AI Kaggle competition assistant with Qdrant RAG and Ollama is a ready-made n8n workflow you import as a workflow JSON file — no build required. It connects agent, chainSummarization, chatTrigger, documentDefaultDataLoader. It's free to download. Follow the 5-step import below to go live in minutes.
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 Qdrant-backed Retrieval-Augmented Generation (RAG). Deploy via containerized starter kit. Needs high end GPU support or patience. Initial chat should contain guidelines on what to to produce and the challenge guidelines. --- Features - Coding Assistance • "Real"-time Python code recommendations, debugging help, and data-science best practices • Multi-turn conversational context - Workflow Automation • n8n orchestration for LLM calls, document ingestion, and external API integrations - Retrieval-Augmented Generation (RAG) • Qdrant vector-database for competition-specific document lookup • On-demand retrieval of Kaggle competition guidelines, tutorials, and notebooks after convertion to HTML and ingestion into RAG - entirly On-Premises for Privacy • Locally hosted LLM (via Ollama) – no external code or data transfer ALIENTELLIGENCE/contentsummarizer:latest for summarizing qwen3:8b for chat and coding mxbai-embed-large:latest for embedding • GPU acceleration required Based on: breakdown documents into study notes using templating mistralai and qdrant/
Download the workflow JSON file after purchase.
Open n8n → click the menu → Import from File.
Select the downloaded JSON and import.
Set up credentials for each node that requires them.
Click Execute Workflow to test, then activate.
Setup guide included
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