athina-ai/rag-cookbooks resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2568 stars · 325 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter notebook cookbooks demonstrating advanced and agentic Retrieval-Augmented Generation (RAG) techniques, progressing from naive RAG to sophisticated methods with references to research papers. It provides ready-to-use implementations and evaluation guidance for developers and researchers building RAG systems.

Use cases

• learn advanced RAG techniques
• implement agentic RAG pipelines
• evaluate RAG system accuracy
• compare vector databases like pinecone and weaviate for RAG
• reduce LLM hallucinations with retrieval-augmented generation
• find RAG research paper implementations
• build a RAG chatbot over private documents

When to choose

• you want runnable notebook examples of advanced and agentic RAG patterns
• you need evaluation guidance alongside RAG implementations
• you want a progression from naive RAG to state-of-the-art techniques with paper references

When to avoid

• you need a production-ready RAG framework rather than educational notebooks
• you want a non-Python stack
• you need maintained library APIs instead of example code

Facets

learning-resource · maturity active

rag llm-inference agent-framework machine-learning large-language-models artificial-intelligence tutorials python cross-platform cookbooks jupyter-notebooks vector-databases langchain agentic-rag embeddings retrieval-augmented-generation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="athina-ai/rag-cookbooks")