Setting Up a Retrieval-Augmented QA Pipeline with Haystack and Ollama
Introduction Retrieval-Augmented Generation (RAG) is a powerful approach for creating more accurate and context-aware responses from Large Language Models (LLMs). Instead of relying solely on the model’s internal training data, RAG uses external documents to ground answers, making them more factual and relevant. In this tutorial, you’ll learn how to build a simple RAG pipeline using Haystack and Ollama. By the end, you’ll have a working setup that retrieves relevant documents and generates answers locally—no expensive API keys required. ...