ragbits and oreilly-retrieval-augmented-gen-ai
One is a set of building blocks for GenAI application development, while the other is an O'Reilly course demonstrating how to augment LLMs with real-time data, thus making them ecosystem siblings since one provides the components for the concepts taught in the other.
About ragbits
deepsense-ai/ragbits
Building blocks for rapid development of GenAI applications
This project offers robust building blocks for quickly creating Generative AI applications. It allows you to feed various document types, like PDFs and spreadsheets, into an AI system to get accurate, context-aware answers. It's designed for AI developers and engineers looking to build scalable and reliable AI assistants, chatbots, or intelligent search tools.
About oreilly-retrieval-augmented-gen-ai
sinanuozdemir/oreilly-retrieval-augmented-gen-ai
See how to augment LLMs with real-time data for dynamic, context-aware apps - Rag + Agents + GraphRAG.
This project helps AI developers build applications that can answer questions using up-to-date, external information. You'll learn how to feed real-time data into large language models (LLMs) to get more accurate and context-aware responses. It's designed for developers with Python skills and some background in machine learning and natural language processing who want to create dynamic, intelligent applications.
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