FareedKhan-dev/rag-ecosystem

Understand and code every important component of RAG architecture

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Established

This project helps AI developers understand and build robust Retrieval Augmented Generation (RAG) systems. It provides practical code examples and explanations for each component, from initial data indexing to advanced query transformations and system evaluation. This is for AI engineers or machine learning practitioners looking to implement or optimize RAG pipelines for their applications.

228 stars. No commits in the last 6 months.

Use this if you are an AI developer who needs to build, customize, or improve a RAG system that delivers accurate and contextually relevant responses.

Not ideal if you are an end-user simply looking to use an existing RAG-powered application without delving into its technical construction.

AI Development Large Language Models Information Retrieval Generative AI ML Engineering

Stale 6m No Package No Dependents

Maintenance 2 / 25

Adoption 10 / 25

Maturity 15 / 25

Community 23 / 25

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Stars

228

Forks

Language

Jupyter Notebook

License

MIT

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rag-ecosystem and bRAG-langchain rag-ecosystem and complex-RAG-guide

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