Leveraging Langchain for a RAG (Retriever Augmented Generation) project, this implementation enables efficient querying across multiple books, enhancing data retrieval and natural language generation for context-rich answers.

A practical collection of examples demonstrating how to use LangChain Document Loaders to ingest data from various sources and transform it into a standardized format for Large Language Model (LLM) applications.

PostCSS loader for loading and processing styles from within HTML templates.

Detailed description given in the README