agentic-rag-for-dummies and Agentic-RAG-R1
These are complements: the first provides a foundational, modular framework for learning and building agentic RAG systems, while the second extends that capability with reinforcement learning-based optimization for agent decision-making.
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 Agentic-RAG-R1
jiangxinke/Agentic-RAG-R1
Agentic RAG R1 Framework via Reinforcement Learning
This framework helps AI/ML researchers and developers enhance the reasoning and search capabilities of their large language models (LLMs). By training a base LLM with reinforcement learning, you can feed in complex questions and external knowledge bases to get back more accurate and contextually rich answers. It's designed for those building advanced AI applications that require autonomous decision-making and deep information retrieval.
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