Loading video player...
LangChain can feel messy until you see how the main building blocks fit together in a single workflow. In this hands-on walkthrough, we build a simple AI application step by step and use it to explain the pieces that LangChain is made of: chains (prompt-to-model pipelines), agents (systems that choose actions and use tools), memory (so your app can remember earlier messages), and loaders (to bring documents and datasets into the workflow). You’ll also see the practical setup that trips people up, like environment variables, API authentication checks, and invoking the model in a multi-turn conversation. If you’ve been copying snippets without really understanding what’s happening, this will make the structure click and give you a clean mental model to build bigger projects from. Get ahead from your peers with Promp Engineering. Enroll for free: https://www.mygreatlearning.com/academy/learn-for-free/courses/prompt-engineering-for-chatgpt?utm_source=CPV_YT&utm_medium=Desc&utm_campaign=Fast_Track_Your_AI_Skills_LangChain_Components_Deep_Dive #LangChain #LLM #OpenAI #GPT35 #AIEngineering #Python #AIAgents #RAG #MachineLearning #GenerativeAI #PromptEngineering #Developer