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agentic-rag-for-dummies

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

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rag-agentsqdrantlangchainagentic-aiagentic-ragollamaagentsbm25pythonllmgradiogenerative-airagagentrag-chatbotai-agentsrag-pipelineJupyter Notebookretrieval-augmented-generation-raglanggraphretrieval-augmented-generation

A GitHub repository containing a modular Agentic RAG (Retrieval-Augmented Generation) pipeline built with LangGraph, presented as a learning project. Its topics and file types indicate it uses Qdrant, BM25, Ollama, LangChain, and a Gradio interface, written in Python/Jupyter Notebook.

You want a small, MIT-licensed reference implementation to learn how agentic RAG pipelines are assembled with LangGraph.

Use it to

  • Study a modular LangGraph-based agentic RAG pipeline
  • Run and modify a RAG chatbot example locally with Ollama
  • Explore hybrid retrieval combining Qdrant and BM25
  • Use the notebooks as a hands-on RAG tutorial

For Developers learning to build agentic RAG systems

Role
rag
Language
Jupyter Notebook
Licence
MIT
Forks
533
Last push
2026-08-30
Latest release
v1.0 · 2025-10-20
topicsagentic-raglanggraphretrieval-augmented-generationqdrantollamalearning