Exploring RAG, LangChain, LangSmith, and LangServe in AI Development Frameworks

The chapter delves into the significance of RAG as a connector between a compute engine and external data sources, emphasizing its continual importance in the AI landscape. It explains the functionalities of LangChain as an application development framework for LLMs, allowing for easy composition of databases and embedding models. Additionally, it discusses LangSmith for observability and LangServe for deploying chains as web apps, alongside the templates available within GraphDB Lang and the user-friendly tooling within LangChain.