ai-agent

RAG_Techniques: Master AI Generation with Proven Strategies

Name: RAG_Techniques: Master AI Generation with Proven Strategies
Author: NirDiamant

Comprehensive tutorial notebooks for advanced retrieval-augmented generation techniques. Perfect for AI founders wanting to level up their language model performance.

27,672 stars3,334 forksJupyter NotebookUpdated 5/31/2026100% free · open source

What it does

Provides technical tutorials and implementations for improving AI language model performance through advanced retrieval strategies

When to use it

•When building AI applications that need more contextually accurate responses
•For startup AI products requiring nuanced, knowledge-specific language generation
•When standard chatbot/LLM outputs are too generic or imprecise

Quick start

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

Topics

agentic-rag

embeddings

generative-ai

gpt

langchain

llama-index

llm

llms

machine-learning

nlp

openai

python

rag

retrieval-augmented-generation

semantic-search

tutorials

vector-database

What's inside — free to inspect

No purchase needed

Read the entire source before you build — unlike paid marketplaces that hide it behind a buy button.

top-level files

folders

38.2M

repo size

Other

license

Key files

README.md

File tree

.github/

all_rag_techniques/

all_rag_techniques_runnable_scripts/

data/

evaluation/

images/

tests/

.gitignore

CONTRIBUTING.md

helper_functions.py

LICENSE

README.md

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Details

Creator

NirDiamant

Language

Jupyter Notebook

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