RAGLight's data source compatibility is reflected in its dual support for local folders and GitHub repositories. Users can easily import local documents such as PDFs and text files, or link directly to publicly available GitHub repositories to automatically extract document content. This feature significantly simplifies the process of building a knowledge base, enabling both individual developers and teams to quickly integrate diverse data sources, providing rich contextual information for subsequent document retrieval and generation tasks.
This answer comes from the articleRAGLight: Lightweight Retrieval Augmentation Generation Python LibraryThe
May not be reproduced without permission:AI productivity tools " RAGLight supports importing data from local folders or GitHub repositories to build knowledge bases.
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