Скачать или смотреть LangChain Explained in 10 Minutes (Components Breakdown + Build Your First AI Chatbot)

🧪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:    • RAG Explained For Beginners  

⏰ 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

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