bragai/bRAG-langchain

Everything you need to know to build your own RAG application

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Established

This project provides comprehensive guides and boilerplate code for building Retrieval-Augmented Generation (RAG) applications. It takes your various documents and a user's question, then processes them to deliver accurate and contextually relevant answers. Developers, machine learning engineers, and data scientists looking to implement or enhance RAG systems will find this useful.

4,051 stars.

Use this if you are a developer or machine learning engineer aiming to build or customize a RAG-powered chatbot or information retrieval system.

Not ideal if you are a non-technical user looking for an out-of-the-box RAG application without needing to write code.

AI-development NLP-engineering chatbot-development information-retrieval LLM-applications

No Package No Dependents

Maintenance 6 / 25

Adoption 10 / 25

Maturity 16 / 25

Community 21 / 25

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Stars

4,051

Forks

480

Language

Jupyter Notebook

License

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

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