agentic-rag-for-dummies and Awesome-RAG-Reasoning
A practical implementation framework for building agentic RAG systems complements B's curated collection of RAG reasoning research and techniques, as one provides executable code while the other provides the theoretical foundations and reasoning strategies to inform that implementation.
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.
About Awesome-RAG-Reasoning
DavidZWZ/Awesome-RAG-Reasoning
[EMNLP 2025] Awesome RAG Reasoning Resources
This collection helps AI researchers and practitioners develop advanced AI systems that can accurately answer complex questions and solve problems. It brings together resources on combining external knowledge retrieval with sophisticated logical thinking, providing a roadmap for building more capable AI agents. Researchers, AI developers, and system architects working on advanced AI applications would use this.
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