Building LLM Agents - PAL, ReAct, and LangChain Implementation Guide

Learn to build advanced LLM agents from scratch in this comprehensive video tutorial that covers essential paradigms like Program-Aided Language models (PAL) and Reason + Act (ReAct). Master manual implementation techniques before exploring the same functionalities using the Langchain framework and LangChain Expression Language (LCEL). Discover how to seamlessly switch between different language models including GPT-4, Llama 3.1, and Mixtral on platforms like TogetherAI and Groq for flexible agent design. Explore OpenAI's function calling as an alternative to direct ReAct prompting, and gain hands-on experience with a provided lab notebook. Progress through structured topics including setup procedures, PAL implementation, LLM chains, ReAct operational loops, various format implementations (JSON, XML), and the development of chat-based ReAct agents for conversational applications.