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Exploring LangChain: A Practical Approach to Language Models and Retrieval-Augmented Generation (RAG)
Last updated: Thursday, December 19, 2024
Published in: CODE Magazine: 2025 - Jan/Feb
Wei-Meng Lee provides an in-depth guide to using the LangChain framework for building applications incorporating large language models (LLMs). He emphasizes LangChain's modular design, enabling developers to create complex workflows with customizable components and integrate external data sources, facilitating Retrieval-Augmented Generation. Key topics covered include constructing chains, maintaining conversational context with memory management, and leveraging Microsoft and Hugging Face's models for enhanced flexibility and privacy. Wei-Meng also demonstrates implementing RAG for document-based querying, offering a comprehensive overview of LangChain's capabilities for developing dynamic, data-driven solutions.