GH Repository · NirDiamant
RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
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Jupyter Notebooksemantic-searchmachine-learningagentic-raglangchaintutorialsllama-indexgenerative-airagnlpllmsgptvector-databaseaipythonllmembeddingsretrieval-augmented-generationopenai
A collection of tutorials covering advanced techniques for Retrieval-Augmented Generation systems. Each technique is presented as a detailed Jupyter notebook walkthrough.
Use it to learn and implement specific RAG techniques through hands-on notebooks rather than assembling them from scattered sources.
Use it to
- Study individual RAG techniques via notebook tutorials
- Explore agentic RAG patterns
- Learn semantic search and embedding workflows
- Compare LangChain and Llama-Index approaches
- Prototype RAG pipelines in Python
For Developers and ML practitioners building RAG systems
- Role
- rag
- Language
- Jupyter Notebook
- Licence
- custom (licence file present)
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- 3,611
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- 1
- Last push
- 2026-09-15
- Latest release
- book-v1.0 · 2026-04-15
topicsragtutorialsembeddingssemantic-searchllmspython