context-aware-rag and Controllable-RAG-Agent
About context-aware-rag
NVIDIA/context-aware-rag
Context-Aware RAG library for Knowledge Graph ingestion and retrieval functions.
This library helps developers enhance their AI applications by creating sophisticated RAG (Retrieval Augmented Generation) pipelines. It takes various data sources, extracts structured knowledge, and outputs relevant information for natural language queries. Developers, AI engineers, and data scientists use it to build context-aware AI agents or Q&A systems.
About Controllable-RAG-Agent
NirDiamant/Controllable-RAG-Agent
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
This project helps people answer complex questions from their documents, like research papers or books, even when the answer isn't obvious. You provide your documents and ask a question, and it gives you a well-reasoned answer based only on your data. Anyone who needs to extract precise, detailed answers from large amounts of text, such as researchers, analysts, or educators, would find this useful.
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work