LLM Apps Framework

In this video, 1littlecoder presents a framework for understanding and building LLM (Large Language Model) applications, categorized into five levels. The framework is visualized as a pyramid, with the base representing the simplest applications and the peak representing the most advanced. The first level involves basic Q&A systems, where users ask questions, and the LLM provides answers. The second level introduces conversational chatbots, which add short-term memory to maintain context in conversations. The third level, Retrieval-Augmented Generation (RAG), incorporates external knowledge and long-term memory, allowing the LLM to access and use additional data sources. The fourth level covers function calling, enabling the LLM to interact with external tools and APIs. The final level, LLM agents, involves multi-agent systems that can perform complex tasks and trigger actions. The video also discusses the potential future of LLMs, including the concept of an LLM operating system (LLM OS), where the LLM serves as the core of an integrated system with short-term and long-term memory, tools, and internet connectivity. The presenter emphasizes the importance of understanding these levels for building effective AI applications and encourages viewers to explore and experiment with these concepts.