Bessouat40/RAGLight
RAGLight is a modular framework for Retrieval-Augmented Generation (RAG). It makes it easy to plug in different LLMs, embeddings, and vector stores, and now includes seamless MCP integration to connect external tools and data sources.
RAGLight helps you quickly build a chatbot that can answer questions using your own documents, like PDFs, Word files, or code. You feed it your collection of files, and it produces a chat interface where you can ask questions and get answers grounded in your specific information. This is ideal for anyone who needs to quickly create a custom AI assistant that understands their unique knowledge base.
655 stars. Actively maintained with 33 commits in the last 30 days.
Use this if you need to build a custom AI assistant that can accurately answer questions by pulling information directly from your specific set of documents, such as internal reports, research papers, or project documentation.
Not ideal if you're looking for a simple, off-the-shelf chatbot that doesn't require connecting to your private data or if you need advanced features beyond document-based question answering.
Stars
655
Forks
99
Language
Python
License
MIT
Category
Last pushed
Mar 13, 2026
Commits (30d)
33
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