This article details building a Retrieval-Augmented Generation (RAG) system to assist with research paper tasks, specifically question answering over a PDF document. It covers document loading, splitting, embedding with Sentence Transformers, using ChromaDB as a vector database, and implementing a query interface with LangChain.
This article provides a step-by-step guide to creating an AI-powered English tutor using Retrieval-Augmented Generation (RAG). It integrates a vector database (ChromaDB) for storing and retrieving relevant English language learning materials and Groq API for generating structured and engaging lessons. The tutorial covers installing necessary libraries, setting up the environment, defining a vector database class, implementing AI lesson generation, and combining vector retrieval with AI generation.
