LangChain Models Component Coding Part 1 | Implementing LLMs with Standardized API Structure скачать в хорошем качестве

LangChain Models Component Coding Part 1 | Implementing LLMs with Standardized API Structure

#LangChain #LLM #GenerativeAI #FoundationModels #AIArchitecture In this video, I begin the coding series on Models in LangChain by first explaining the real-world problem behind LLM integration. Before writing code, it is important to understand: • Why building foundation models requires massive data, hardware, cost, and expert teams • Why not everyone can build their own LLM • How large companies release their models via APIs • The challenge of different API structures across providers • How LangChain solves this problem by providing a universal interface for LLMs This video focuses on building complete conceptual clarity before moving into practical implementation. Understanding this abstraction layer is critical before working with OpenAI, Anthropic, or other model providers inside LangChain. In the next videos, I will start implementing different models using code examples. This is part of my LangChain for GenAI Developers series, where I am building LLM-based systems step by step — from architecture to implementation. If you want to understand AI systems beyond just tutorials, this series will help you build strong foundations. #LLM #LangChainTutorial #AIArchitecture #GenAI #AIDevelopment #LLMDevelopment #FoundationModels #BuildAIApps