Components of LangChain Explained | LangChain Architecture for Beginners (with Examples)

Description

In this video, we’ll break down the core components of LangChain — the powerful framework that helps you build applications with Large Language Models (LLMs). You’ll learn: 🧠 What is LangChain? ⚙️ Key components — Models, Prompts, Memory, Chains, Tools, Agents, and Retrievers 🧩 How these components work together to build intelligent AI workflows 💬 Real examples using OpenAI, Hugging Face, and Groq Perfect for students, developers, and anyone exploring LLMs, RAG, and AI app development! 📌 GitHub Repository (Code + Notes): 👉 https://github.com/dearnidhi/Agentic-AI-HandsOn-Bootcamp 📩 Contact: ✉️ Email: nidhiyachouhan12@gmail.com 💼 LinkedIn: https://www.linkedin.com/in/nidhi-chouhan-544650b4/ 📸 Instagram: @dear_nidhi | @codenidhi ✨ Don’t forget to LIKE 👍, SHARE 📢, & SUBSCRIBE 🔔 for more AI & LangChain tutorials! #codenidhi #nidhichouhan #LangChain #LLM #AIagents #RAG #LangGraph #promptengineering #chainsofthought #AItutorial #PythonAI #LangChainForBeginners #AIworkflow #AgenticAI langchain components, langchain architecture, langchain tutorial for beginners, langchain explained, what is langchain, langchain tools, langchain chains, langchain memory, langchain prompts, langchain agents, langchain retriever, langchain groq, langchain openai, langchain huggingface, agentic ai, rag tutorial, ai developer guide, build llm apps, python langchain, langchain graph