R
RAG_Techniques
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 Notebook
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📋 Project at a Glance
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What's this?A agentic-rag/embeddings tool in the Data & Infrastructure category, built with Jupyter Notebook, open-source
Who made it?Maintained by NirDiamant team, 29K⭐ on GitHub, #59 out of 3133 in Data & Infrastructure
Why does it exist?With the growing demand for agentic-rag and embeddings in Data & Infrastructure, NirDiamant created RAG_Techniques as a streamlined solution.
What can it do?Key use cases: generative-ai, gpt, langchain
How to install with AI?Use an AI coding assistant to follow the README and automatically handle the install and environment setup.
🔗 github.com/NirDiamant/RAG_Techniques | 官网 https://diamant-ai.com
🔗 github.com/NirDiamant/RAG_Techniques | 官网 https://diamant-ai.com
Topics
agentic-ragaiembeddingsgenerative-aigptlangchainllama-indexllmllmsmachine-learningnlpopenaipythonragretrieval-augmented-generationsemantic-searchtutorialsvector-database