RAG Components in LangChain | Document Loaders, Text Splitters, Indexes, Vector Stores & Retrievers скачать в хорошем качестве

RAG Components in LangChain | Document Loaders, Text Splitters, Indexes, Vector Stores & Retrievers

#LangChain #RAG #GenerativeAI In this video, I explain the core components required to build a RAG (Retrieval-Augmented Generation) system in LangChain. If you're building LLM-based applications, understanding these foundational components is essential before implementing a complete RAG pipeline. 🔎 Topics Covered: • What is RAG (Retrieval-Augmented Generation) • Document Loaders • Text Splitters and chunking strategies • Embeddings (concept overview) • Indexes in LangChain • Vector Stores • Retrievers • How the retrieval process works in AI applications This video focuses only on the architecture and building blocks of a RAG system using these components. This is part of my LangChain for GenAI Developers series, where I share everything I learn step by step — from theory to implementation. If you want to build production-ready AI applications, mastering these RAG components is essential. #RetrievalAugmentedGeneration #LangChainTutorial #VectorStore #Indexes #DocumentLoader #LLMApplications #AIApplications #GenAI #BuildAIApps