LangSmith

👉Get 40% OFF CodeCrafters: https://app.codecrafters.io/join?via=codehead-01 👉Git gud at coding with Scrimba https://scrimba.com/?via=codehead (20% OFF with this link) 👉ACE your next technical interview with 50% OFF AlgoMonster: https://algo.monster/codehead 👉I made a Discord server for all of you code heads to join: https://discord.gg/MfCKFK2fTe 👉Buy this tired Code Head a ☕: https://buymeacoffee.com/codehead ❓Topics covered: What is LangChain? How to install LangChain? How to use LangChain? How LangChain works? Chains and workflows Prompt templates LangChain Memory Tools and Agents RAG basics Document embeddings Vector databases Model swapping (OpenAI, Anthropic, local) LangGraph overview LangChain use cases #ai #langchain #programming

🧪Try LangChain Hands-on Labs for Free: https://kode.wiki/462mo31 Building a company chatbot that remembers conversations, accesses your knowledge base, and provides intelligent responses seems overwhelming - but LangChain makes it surprisingly simple. In this comprehensive video, you'll discover why LangChain has become the go-to framework for building production-ready AI agents. We break down the key differences between raw LLMs and intelligent agents, showing you exactly why traditional approaches fall short when building real-world applications. 🎯 What You'll Learn: • The critical components every AI agent needs (LLM, memory, tools, vector database, RAG) • How LangChain simplifies complex AI workflows • Why vendor independence matters (easily switch from OpenAI to Anthropic to Gemini) • Building chat pipelines with LangChain Expression Language (LCEL) • RAG implementation for knowledge retrieval from company documents • Complete deployment process for production-ready chatbots 🚀 Hands-On Labs Included: Follow along with our free interactive labs where you'll build a complete chatbot from installation to deployment. We cover prompt piping, model chaining, memory systems, and RAG implementation with real code examples you can run immediately. 🧪Try LangChain Hands-on Labs for Free: https://kode.wiki/462mo31 📌 Learn more about RAG here: https://youtu.be/_HQ2H_0Ayy0 ⏰ VIDEO TIMESTAMPS: 00:00 - Introduction: Why You Need LangChain? 00:58 - LLMs vs AI Agents Explained 02:05 - Traditional Software vs Agentic Software 02:29 - LangChain Core Components 03:36 - Traditional Software vs Agentic Software 04:47 - Practical Lab Demo Introduction 05:20 - Demo - Install LangChain Ecosystem 06:00 - Demo - Prompt Templates 08:49 - Demo - LCEL (LangChain Expression Language) 10:00 - Demo - Memory Systems & RAG Implementation 11:14 - Deploying Your Production Chatbot 🔔 SUBSCRIBE for cutting-edge AI tutorials that actually matter! #LangChain #AIAgents #AIchatbot #OpenAI #AI #Chatbot #PythonProgramming #Langgraph #LangChaintutorial # #LLM #AIagents #Anthropic #BuildChatbot #AItools #kodekloud