Exploring LangChain: A Practical Approach to Language Models and Retrieval-Augmented Generation (RAG)

The article in CODE Magazine introduces LangChain, a framework for building applications with large language models (LLMs). LangChain simplifies embedding LLMs into workflows for conversational agents, knowledge retrieval systems, and more. The article provides a basic example of using LangChain components like PromptTemplate, ChatOpenAI, and StrOutputParser to create a conversational application. It also explores maintaining conversation memory, chunking text for efficient processing, and using alternative models like Hugging Face for privacy concerns. Additionally, the article delves into implementing Retrieval-Augmented Generation (RAG) for document-based querying, showcasing the practical applications of LangChain in natural language processing tasks. [Extracted from the article]