a local RAG LLM with persistent database to query your PDFs

Chat with your documents locally

Free, local, open-source RAG with Mistral 7B LLM, using local documents.

Local LLM with Ollama & PgVector made for Llama3.

Local agentic Rag implementation with local models and fine tuning

Complete AI assistant running locally with free llms provider, and with SOTA RAG techniques.

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A fully local RAG (Retrieval-Augmented Generation) demo showcasing Weaviate vector database with Ollama for embeddings and generation, optimized for Qualcomm Snapdragon X Elite on Windows WSL.

R&D for best local RAG

LocalRAGSystem - a local rag system with models ollama/openai (switchable) , tracable with phoenix , docker runing backend api , openwebview as UI , llamaindex embeddding ,

Trying out LocalRag approach from Arafat Tehsin

A simple tutorial showing how to set up a completely local RAG + LLM with LM Studio to ask questions about your own files (PDF, DOCX, TXT, MD, CSV) using less than 2.5GB of memory.

Minimal, fully local Python-based app for question answering over PDF documents. Uses FastAPI, React, Qdrant, and Ollama. Easily extensible to other file types and models. No cloud required—your data stays private.

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LocalRAG

Terminal LLM Interface with Infinite Memory

LocalRAGify is a zero-cost, local RAG chatbot built with open-source tools like OpenSearch for retrieval and Ollama for generative AI. It enables you to create and deploy an AI assistant on your own machine with a simple, user-friendly interface powered by Streamlit. No cloud or paid services required.

Fast local RAG toolkit with Go backend for speed. zero cloud, runs on potato hardware

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Local and private RAG system

Self-hosted RAG

A fully local RAG (Retrieval-Augmented Generation) system for privacy-preserving document search and question answering. Run it from any project directory to index and query your documents using local LLMs.

Query your documents locally with AI — no cloud, no API keys.

A fully local RAG system powered by Zvec — search your documents with natural language, no API keys required.

Local mcp tool to index and expose local pdf files for LLM applications

Demo of how to get local chat going with folders of content. v1: Claude Conversations

Offline Conversational AI using RAG, FAISS, and Local LLMs Llama3.2 via Ollama

LocalRAG is a fast and modular Retrieval-Augmented Generation pipeline built for usage on consumer hardware.

This is is the barebones implementation of the RAG for Llms.