Learn how to build interactive AI chat applications using Streamlit and LangChain in this 32-minute tutorial. Explore the power of LangChain's Agent, which delegates tasks to specialized tools like calculators, web browsers, and translators. Discover how to leverage action agents for step-by-step decision-making and plan-and-execute agents for upfront action planning. Combine these capabilities with Streamlit, a popular Python-based web app framework, to create fast and interactive AI-powered applications. Gain insights into LangChain Agents, Streamlit's features, and the MRKL paper. Access additional resources and related tutorials in the LangChain/LLM series to further enhance your understanding of large language models and their applications.