Learn how to build real-world AI agents using frameworks like LangChain, LangGraph, CrewAI, and AutoGen. This playlist covers agent architectures, workflows, tool calling, memory, and real-world use cases — from beginner to advanced. Perfect for AI engineers, developers, and system design learners. #AIAgents #GenerativeAI #LangChain #AIEngineering
Curated by: Naveen Tech Hub (38 videos)
Learn the difference between LangChain PromptTemplate and ChatPromptTemplate with practical Python examples. In this 5-minute tutorial, we build a customer support assistant example to show how prompt templates, chat messages, and conversation history work. You’ll learn: • When to use PromptTemplate vs ChatPromptTemplate • How to pass variables and inspect formatted prompts • System and human message roles • HumanMessage vs HumanMessagePromptTemplate • How MessagesPlaceholder handles supplied conversation history • How to connect a prompt, chat model, and output parser • Common mistakes: missing variables and escaping JSON braces • Best practices for trusted templates, history limits, and output validation The walkthrough uses langchain_core and a FakeListChatModel for practice without an API key. We also explain where a configured chat model fits into the pipeline. Ideal for Python developers and beginners learning LangChain, prompt engineering, and AI chatbot development. Try it yourself: add a language variable and test English and Hindi replies. Subscribe to Naveen TechHub for practical AI tutorials and coding walkthroughs. Official LangChain references: https://reference.langchain.com/python/langchain-core/prompts/prompt/PromptTemplate https://reference.langchain.com/python/langchain-core/prompts/chat/ChatPromptTemplate https://reference.langchain.com/python/langchain-core/prompts/chat/MessagesPlaceholder #LangChain #PromptEngineering #PythonTutorial #NaveenTechHub