RAG for Local LLM, chat with PDF/doc/txt files, ChatPDF. 纯原生实现RAG功能，基于本地LLM、embedding模型、reranker模型实现，支持GraphRAG，无须安装任何第三方agent库。

Fullstack "Chat with your PDFs" RAG (Retrieval Augmented Generation) app built fully on Cloudflare

A full-stack demo showcasing a local RAG (Retrieval Augmented Generation) pipeline to chat with your PDFs.

Completely local RAG. Chat with your PDF documents (with open LLM) and UI to that uses LangChain, Streamlit, Ollama (Llama 3.1), Qdrant and advanced methods like reranking and semantic chunking.

Simple Chainlit UI for running llms locally using Ollama and LangChain

SmartRAG is a privacy-first multimodal RAG system that lets you chat intelligently with your documents, images, and audio. Upload PDFs, Word files, or recordings and get accurate, context-aware answers all processed locally on your device with no external APIs.

Chat with PDF using LangChain, Streamlit, Ollama (for LLM inference) and PDFPlumber. Overall which is an example of a Retrieval-Augmented Generation (RAG) system with Deepseek r1 model.

RAG (Retrieval-Augmented Generation) template with PDF OCR, vector search and chat/documents UI

JARVIS Chatbot: a local simple RAG assistant with PDF files

Simple demo for chatting with a PDF - and optionally point the RAG implementation to a local LLM

Local RAG + offline LLM demo with Streamlit chat UI, FAISS vector DB, and LoRA tuning/merge utilities — fully powered by Ollama models running locally. Tech Stack: Python 3.11+ · Streamlit · FAISS · Ollama (local LLM + embeddings) · nomic-embed-text · qwen2.5-instruct · PDF ingestion + chunking · LoRA fine-tuning helpers

A RAG demo using LangChain that allows you to chat with your uploaded PDF documents

This is a RAG project to chat with your uploaded PDF , made using Langchain and Anthropic Claude 3 used as LLM , hosted using Streamlit

Spring AI demo backend with chat, tool calling, multimodal input, PDF RAG, and conversation history management.

Vortex is a self-hosted RAG (Retrieval-Augmented Generation) application that lets you chat with your documents using any LLM provider. Upload PDFs, ingest URLs, and get accurate answers grounded in your own knowledge bases — all with a clean, modern interface.

Build a LLM app with RAG to chat with PDF using Llama 3.2 running locally on your computer

This project is a Streamlit-based web app that lets you upload multiple PDF documents and interact with them in natural language. It uses Google Gemini (via LangChain) for embeddings and question-answering, along with FAISS as the vector store for efficient document retrieval.

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Chat with your PDFs using AI! This Streamlit app uses RAG, LangChain, FAISS, and OpenAI to let you ask questions and get answers with page and file references.

This application allows users to upload PDF files, process them, and ask questions about the content using a locally hosted language model. The system uses Retrieval-Augmented Generation (RAG) to provide accurate answers based on the uploaded PDFs.

A Multimodal RAG System powered by Qwen-VL. Chat with PDFs, Images, and Text seamlessly using FastAPI & Streamlit.

LexReviewer is an AI legal document review engine that ingests PDFs, uses RAG for hybrid retrieval, and enables grounded chat with citations and bounding-box references, delivering verifiable answers directly from the source text.

Simple RAG chatbot built with LangChain and Ollama that chats with your own PDFs. Blog post: https://medium.com/@tschechd/retrieval-augmented-generation-rag-in-practice-implementing-a-chatbot-with-langchain-and-ollama-79d6d19642f7

A RAG application for chatting with PDF files.

A RAG demo using LangChain that allows you to chat with your uploaded PDF documents

AI chatbot with multiple trending LLMs and a RAG option to chat with your PDF documents

RAG system for chatting with documents using OpenAI & Anthropic, supports PDF/DOCX/TXT/MD with semantic search and source citations

Chat with your PDFs using AI! This Streamlit app uses RAG, LangChain, FAISS, and OpenAI to let you ask questions and get answers with page and file references.

🕸️ Open-source NotebookLM alternative with infinite canvas | Self-hosted Google NotebookLM replacement | RAG chat + PDF/Webpage/Video | Any LLM

Develop an end-to-end Retrieval-Augmented Generation (RAG) system to create a 'Document Search' application, enabling users to chat with their own data from PDFs and text files. This project emphasizes modular coding for production-ready AI applications, utilizing UV for environment setup and comprehensive data lifecycle management.