RAG_Techniques: Boost AI Generation
Get advanced Retrieval-Augmented Generation techniques with detailed tutorials, for founders using AI and NLP, with 28k+ GitHub stars
27,727 stars3,345 forksJupyter NotebookQuality 8/10Updated 6/5/2026100% free ยท open source Provides technical tutorials and implementations for improving AI language model performance through advanced retrieval strategies
- โขWhen building AI applications that need more contextually accurate responses
- โขFor startup AI products requiring nuanced, knowledge-specific language generation
- โขWhen standard chatbot/LLM outputs are too generic or imprecise
- 1Clone the GitHub repository
- 2Install required Jupyter/Python dependencies
- 3Open specific technique notebooks matching your use case
- 4Run example code and experiment with your own datasets
Ready-to-paste prompt git clone https://github.com/NirDiamant/RAG_Techniques && cd RAG_Techniques && pip install -r requirements.txt
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Topics
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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