Bbs1412/rag-with-gemma3
This project is a modular Retrieval-Augmented Generation (RAG) system built with Google DeepMind's - Gemma 3 served locally using Ollama.
This project helps individuals understand and chat with their own documents, such as PDFs, text files, or Markdown. You upload your documents, and then you can ask questions about their content in plain language. It's ideal for anyone who needs to quickly extract information or discuss details from a collection of personal or shared documents.
No commits in the last 6 months.
Use this if you need to privately and interactively query your own collection of documents using a local AI model, without sending your data to external services.
Not ideal if you need to analyze highly structured data like spreadsheets or databases, or if you're looking for a broad internet search tool.
Stars
11
Forks
2
Language
Python
License
GPL-3.0
Category
Last pushed
Jul 04, 2025
Commits (30d)
0
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