Build an On-Premises AI Kaggle Competition Assistant with Qdrant RAG and Ollama

## Step 2. Summarise and Vectorise Document Contents
[Learn more about using the Qdrant VectorStore](https://docs.n8n.io/integrations/builtin/cluster-nodes/root-nodes/n8n-nodes-langchain.vectorstoreqdrant)

Capturing the document into our vector store is intended for a technique we'll use later known as Retrieval Augumented Generation or "RAG" for short. For our scenario, this allows our LLM to retrieve context more efficiently which produces better respsonses.