ngshya/easyRAG
Build your own RAG and run it locally on your laptop: ColBERT + DSPy + Streamlit
This project guides you through creating a system that can answer questions based on your own documents. You feed it a collection of text documents and then ask questions, receiving informed answers. This is ideal for developers who want to learn and implement their first Retrieval Augmented Generation (RAG) system locally.
No commits in the last 6 months.
Use this if you are a developer new to Generative AI and want a step-by-step tutorial to build a local RAG system for question-answering.
Not ideal if you're a non-technical user looking for a ready-to-use application, or if you need an enterprise-grade, scalable RAG solution.
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Language
Python
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Last pushed
Mar 14, 2024
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