L14 | Document Loaders in LangChain | Generative AI with LangChain

Description

Master LangChain framework in this Generative AI series. In this video you'll learn: How to use Document Loaders in LangChain to ingest data from various sources TextLoader to load .txt files Example using PyPDFLoader to load PDFs Example using CSVLoader to load CSV files Using WebBaseLoader to load data from URLs Using DirectoryLoader to load files from a directory In this complete Generative AI with LangChain master class: Learn the foundation- Models, PromptTemplates, Messages, LangChain Expression Language (LCEL), Structured Output, Output Parsers with code examples Building blocks for RAG- Document Loaders, Text splitters, Embeddings, Vector Stores, Retrievers. Building RAG Pipeline Read more here: https://www.netjstech.com/2026/04/document-loaders-langchain-examples.html Github Link- https://github.com/netjs/langchainproj/tree/main/L5-DocumentLoaders Please Like | Share | SUBSCRIBE Channel..! @netjstech #langchain #ai #python #generativeai #aiagents #rag