RAGLight and RAG-LLM-using-AI-Pipeline-with-streamlit-interface
RAGLight is a general-purpose RAG framework that could serve as the underlying infrastructure for the kind of financial document processing pipeline that the second tool implements, making them complements rather than competitors.
About RAGLight
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.
About RAG-LLM-using-AI-Pipeline-with-streamlit-interface
Dono1901/RAG-LLM-using-AI-Pipeline-with-streamlit-interface
A system that combines Retrieval-Augmented Generation (RAG), the Claude Sonet 3.5 LLM, and the Pathway framework to analyze financial reports and tables. It ingests data from Google Drive, processes both structured and unstructured formats in real time, and presents insights via a Streamlit-powered interface.
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