GH Repository · athina-ai
rag-cookbooks
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
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agent-frameworkJupyter Notebookweaviateaichromadbtutorialsfaissllmscookbookslangchainragopenaipineconellmpythonqdrant
A collection of Jupyter Notebook cookbooks demonstrating advanced Retrieval-Augmented Generation techniques, maintained by athina-ai. The notebooks are built around Python with vector stores like ChromaDB, FAISS, Pinecone, Qdrant, and Weaviate, plus LangChain and OpenAI.
It gives you working, runnable notebooks for trying multiple RAG techniques and vector store stacks instead of assembling examples yourself.
Use it to
- Learn advanced RAG techniques from runnable notebooks
- Compare vector stores like ChromaDB, FAISS, Pinecone, Qdrant, and Weaviate
- Prototype RAG pipelines with LangChain and OpenAI
- Adapt cookbook code into your own RAG applications
For Developers and researchers building or learning RAG systems
- Role
- agent-framework
- Language
- Jupyter Notebook
- Licence
- MIT
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- 328
- Open issues
- 6
- Last push
- 2025-02-17
topicsragjupyter-notebooksvector-databaseslangchainllmtutorials