ragbits and agentic-rag-for-dummies
These are complementary but positioned at different abstraction levels: ragbits provides lower-level building blocks for production RAG systems, while agentic-rag-for-dummies offers a higher-level reference implementation using LangGraph that demonstrates how to assemble those patterns into a complete agentic system.
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 agentic-rag-for-dummies
GiovanniPasq/agentic-rag-for-dummies
A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.
This project helps developers build advanced AI assistants that can intelligently answer questions using custom data. It takes your documents (like PDFs or Markdown files) and processes them into a searchable format, then uses an AI to interpret user questions, find relevant information, and generate clear, coherent answers. It's designed for AI developers or data scientists who want to create sophisticated conversational agents.
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