📝 Build Your Local RAG System with LLMs

Welcome to the Local LLM-based Retrieval-Augmented Generation (RAG) System! This repository provides the full code to build a private, offline RAG system for managing and querying personal documents locally using a combination of OpenSearch, Sentence Transformers, and Large Language Models (LLMs). Perfect for anyone seeking a privacy-friendly solution to manage documents without relying on cloud services.

🌟 Key Features:

• Privacy-Friendly Document Search: Search through personal documents without uploading them to the cloud.
• Hybrid Search with OpenSearch: Uses both traditional text matching and semantic search.
• Easy Integration with LLMs: Leverage local LLMs for personalized, context-aware responses.

🚀 Get Started

1. Clone the repo: git clone https://github.com/JAMwithAI/build_your_local_RAG_system.git
2. Install dependencies: pip install -r requirements.txt
3. Configure constants.py for embedding models and OpenSearch settings.
4. Run the Streamlit app: streamlit run welcome.py

📘 Blog Guide

For a detailed walkthrough of the setup and code, check out our blog:

Build a Local LLM-based RAG System for Your Personal Documents - Part 1

Build a Local LLM-based RAG System for Your Personal Documents - Part 2: The Guide

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Enjoy your journey in building a private, AI-driven document management system! If you find this project useful, consider sharing it with others in the community!