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NirDiamant/RAG_Techniques
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook… Why it matters: relevant for grounding LLMs in your own data.
GitHub description: This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Stars
30k
Last 24h
+36est.
Last 7 days
+254est.
Forks
3.7k
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[](https://ossradar.net/repo/NirDiamant/RAG_Techniques)<a href="https://ossradar.net/repo/NirDiamant/RAG_Techniques"><img src="https://ossradar.net/badge/NirDiamant/RAG_Techniques" alt="Trending on OSS Radar"></a>About RAG_Techniques
NirDiamant/RAG_Techniques is a Jupyter Notebook project in the RAG / vector category, created 2 years ago. It has 30k GitHub stars and 3.7k forks, and gained +254 stars over the last 7 days (early estimate), ranking #12 of 12 RAG / vector repos tracked by OSS Radar this week.
See more trending RAG / vector repos or the top AI repos this week.
- Language
- Jupyter Notebook
- Category
- RAG / vector
- Created
- Jul 13, 2024
- Last push
- Oct 11, 2026
- agentic-rag
- ai
- embeddings
- generative-ai
- gpt
- langchain
- llama-index
- llm
- llms
- machine-learning
- nlp
- openai
- python
- rag
- retrieval-augmented-generation
- semantic-search
- tutorials
- vector-database
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