Beyond Training Data: Building Document-Aware Chatbots with RAG

RAG (Retrieval-Augmented Generation) solves a critical limitation of language models by allowing them to answer questions grounded in custom documents. This guide demonstrates how Python developers can build intelligent chatbots that understand proprietary knowledge bases instead of relying solely on training data. As organizations increasingly need trustworthy AI systems anchored in their own data, RAG has become essential for creating domain-specific, source-aware AI assistants.